source("0_helpers.R")
knitr::opts_chunk$set(warning = FALSE, message = FALSE)

load("data/cleaned.rdata")

knitr::opts_chunk$set(echo = FALSE, error = TRUE, dev = "CairoPNG",
                      cache = FALSE)
library(ggplot2)
theme_set(theme_bw())

library(codebook)

attributes(s3_daily$grooming_broad)$scale_item_names <- NULL
s3_daily <- s3_daily %>% filter(!is.na(session), !is.na(created))
# s3_daily <- s3_daily %>% select(-!!names(lab))
s3_daily <- s3_daily %>% ungroup()
s3_daily$sleep_fell_asleep_time <- as.numeric(s3_daily$sleep_fell_asleep_time)
s3_daily$sleep_awoke_time <- as.numeric(s3_daily$sleep_awoke_time)
s3_daily$DAL <- as.numeric(s3_daily$DAL)
s3_daily$window_length <- as.numeric(s3_daily$window_length)
attributes(s3_daily$menstruation_imputed)$names <- NULL
attributes(s3_daily$menstruation)$names <- NULL
vars <- c("session", "short", "created_date", setdiff(names(s3_daily), names(lab)))
s3_daily <- s3_daily[, vars]

library(future)
if (file.exists("codings/reliabilities_new.rdata")) {
  load("codings/reliabilities_new.rdata")
  } else {
    library(future.batchtools)
  # plan(tweak(multicore, workers = 3))
  login <- tweak(remote, workers = "arslan@arc-lin-cpt10.mpib-berlin.mpg.de") # Your username goes before the @
  plan(list(login, tweak(multicore, workers = 10))) # this tells the future package that we want to use a remote server for running our future operations
  
  # login <- tweak(remote, workers = "arslan@tardis.mpib-berlin.mpg.de")
  # qsub <- tweak(batchtools_torque, template = 'torque-lido.tmpl', 
  #             # workers = "export LSF_ENVDIR=/opt/lsf/conf",
  #                 resources = list(job.name = 'multilevel_reliability',
  #                                 queue = 'default',
  #                                 walltime = "5:0:0",
  #                                 memory = 32, #gb
  #                                 ncpus = 1))
  # ## Specify future topology
  # ## login node -> { cluster node (compile brms model) } -> { run chains on multiple cores }
  # plan(list(
  #   login,
  #   qsub
  # ))
  
  reliabilities_diary = future::value(future({
      reliabilities_diary <- codebook::compute_reliabilities(s3_daily, 'repeated_many')
      save(reliabilities_diary, file = "codings/reliabilities_new.rdata")
      reliabilities_diary
  }))
  save(reliabilities_diary, file = "codings/reliabilities_new.rdata")
}

plan(multicore)

Demographics

Participants filled out these surveys before being invited to the daily diary. After finishing them, they were invited to fill out the diary on the next day.

Metadata

Description

Dataset name: s1_demo

The dataset has N=1660 rows and 114 columns. 0 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
created
modified
ended
expired
info_study
lab_code
age
gender
gender_other
education_years
education_level
education_level_special
occupational_status
occupation
net_income
study_major
postal_code
religion
religiosity
sex_orientation
sex_orientation_special
relationship_status
relationship_count
relationship_details
duration_relationship_years
duration_relationship_month
partner_gender
partner_gender_other
age_partner
abode_with_partner
abode_flat_share
abode_flat_share_description
abode_alone
abode_special_case_description
long_distance_relationship
distance_partner
days_same_place_partner_monthly
days_with_partner
nights_with_partner
has_children
nr_children
partner_father
family_description_optional
pregnant
breast_feeding
pregnant_stress
pregnant_trying
wish_for_children
contraception_at_all
contraception_other_reasons_not_to
contraception_method
contraception_method_other
contraception_combi
contraception_method_combination_other
contraception_calendar_abstinence
contraception_hormonal_pill
other_pill_name
contraception_hormonal_other
contraception_hormonal_other_name
contraception_pill_estrogen
contraception_pill_gestagen_type
contraception_pill_gestagen
contraception_other_estrogen
contraception_other_gestagen_type
contraception_other_gestagen
contraception_app
contraception_app_name
hormonal_contraception_last3m
contraception_meeting_partner
self_rated_health
height
weight
hormonal_med
hormonal_med_name
psychoactive_med
psychoactive_med_name
alcohol_weekly
cigarettes_daily
sport_weekly
sport_kinds
meat_eating
menarche
menarche_certainty
number_sexual_partner
number_sexual_partner_certainty
first_time
first_time_certainty
mother_menopause_yes
mother_menopause_age
mother_menopause_certainty
menopause_yes
menopause_age
menopause_certainty
menstruation_regular
menstruation_last
menstruation_last_certainty
menstruation_length
menstruation_length_certainty
menstruation_regularity
menstruation_regularity_certainty
free_not_covered
hetero_relationship
short
ended_date
contraception_other_pill_estrogen
contraception_other_pill_gestagen
contraception_other_pill_gestagen_type
hormonal_contraception
contraception_method_broad
contraception_hormonal_pill_estrogen
contraception_hormonal_pill_gestagen_type
estrogen_progestogen
living_situation

Survey overview

1607 completed rows, 1651 who entered any information, 9 only viewed the first page. There are 9 expired rows (people who did not finish filling out in the requested time frame). In total, there are 1660 rows including unfinished and expired rows.

There were 1660 unique participants, of which 1607 finished filling out at least one survey.

This survey was not repeated.

The first session started on 2016-05-02 17:00:26, the last session on 2017-01-13 13:20:58.

Starting date times

People took on average 1702.97 minutes (median 11.07) to answer the survey.

Duration people took for answering the survey

#Variables

info_study

Wie sind Sie auf unsere Studie aufmerksam geworden?

Distribution

Distribution of values for info_study

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_one	info_study	Wie sind Sie auf unsere Studie aufmerksam geworden?	0			2

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4
5	5
6	6

lab_code

Nehmen Sie auch an unserer Laborstudie Attraktivitätsbeurteilungen in Göttingen teil und haben einen Code für diese Studie erhalten? Wenn ja, geben Sie bitte hier unbedingt Ihren persönlichen Code ein. Wenn nein, lassen Sie dieses Feld einfach aus.

Distribution

Distribution of values for lab_code

1453 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
lab_code	Nehmen Sie auch an unserer Laborstudie Attraktivitätsbeurteilungen in Göttingen teil und haben einen Code für diese Studie erhalten? Wenn ja, geben Sie bitte hier unbedingt Ihren persönlichen Code ein. Wenn nein, lassen Sie dieses Feld einfach aus.	text	character	1			3	1453	0.1247	162	0	2	15	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	lab_code	Nehmen Sie auch an unserer Laborstudie Attraktivitätsbeurteilungen in Göttingen teil und haben einen Code für diese Studie erhalten? Wenn ja, geben Sie bitte hier unbedingt Ihren persönlichen Code ein. Wenn nein, lassen Sie dieses Feld einfach aus.	1			3

Value labels

Response choices
name	value

age

Ihr Alter

Distribution

Distribution of values for age

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	18,120,1	age	Ihr Alter	0			4

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

gender

Ihr Geschlecht

Distribution

Distribution of values for gender

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	gender	Ihr Geschlecht	0			5

Value labels

Response choices
name	value
weiblich	1
anderes	2
Item was never rendered for this user.	NA

gender_other

anderes:

Distribution

Distribution of values for gender_other

1658 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
gender_other	anderes:	text	character	1	gender == 2		6	1658	0.0012	2	0	8	49	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	gender_other	anderes:	1	gender == 2		6

Value labels

Response choices
name	value

education_years

Wie viele Bildungsjahre (Schule, Studium an Universität oder FH, Jahre als Doktorand/in, NICHT Berufsschule etc.) haben Sie hinter sich?

Distribution

Distribution of values for education_years

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,26,1	education_years	Wie viele Bildungsjahre (Schule, Studium an Universität oder FH, Jahre als Doktorand/in, NICHT Berufsschule etc.) haben Sie hinter sich?	0			7

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

education_level

Was ist ihr höchster, bislang erreichter Bildungsgrad

Distribution

Distribution of values for education_level

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		education_level	Was ist ihr höchster, bislang erreichter Bildungsgrad	0	mc_vertical			8

Value labels

Response choices
name	value
1	0_not_finished
2	1_hauptschule
3	2_realschule
4	3_polytechnic
5	4_professional_school
6	5_fachabitur
7	6_abitur
8	7_vocational_uni_bachelor
9	8_uni_bachelor
10	9_vocational_uni_master_level
11	10_uni_master_level
12	11_uni_doctorate
13	12_uni_habilitation

education_level_special

Haben Sie einen Bildungsgrad, der sich hier nicht gut einsortieren lässt (bspw. Meister)? Wenn die obige Liste nicht ausreicht, können Sie das hier frei ergänzen.

Distribution

Distribution of values for education_level_special

1562 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
education_level_special	Haben Sie einen Bildungsgrad, der sich hier nicht gut einsortieren lässt (bspw. Meister)? Wenn die obige Liste nicht ausreicht, können Sie das hier frei ergänzen.	textarea	character	1			9	1562	0.059	89	0	1	137	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	education_level_special	Haben Sie einen Bildungsgrad, der sich hier nicht gut einsortieren lässt (bspw. Meister)? Wenn die obige Liste nicht ausreicht, können Sie das hier frei ergänzen.	1			9

Value labels

Response choices
name	value

occupational_status

Welchen beruflichen Status haben Sie derzeit?

Distribution

Distribution of values for occupational_status

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_multiple		occupational_status	Welchen beruflichen Status haben Sie derzeit?	0			10

Value labels

Response choices
name	value
1	not_working
2	pupil
3	trainee
4	student
5	homemaker
6	employed
7	intern

occupation

Welchen Beruf üben Sie aus?

Distribution

Distribution of values for occupation

1187 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
occupation	Welchen Beruf üben Sie aus?	textarea	character	0	occupational_status %contains% “employed”		11	1187	0.2849	384	0	1	282	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	occupation	Welchen Beruf üben Sie aus?	0	occupational_status %contains% “employed”		11

Value labels

Response choices
name	value

net_income

Wie viel Geld haben Sie monatlich zur Verfügung (netto)?

Distribution

Distribution of values for net_income

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		net_income	Wie viel Geld haben Sie monatlich zur Verfügung (netto)?	0			12

Value labels

Response choices
name	value
1	euro_lt_500
2	euro_500_1000
3	euro_1000_2000
4	euro_2000_3000
5	euro_gt_3000
6	dont_tell

study_major

Was studieren Sie derzeit oder haben Sie studiert?

Distribution

Distribution of values for study_major

232 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
study_major	Was studieren Sie derzeit oder haben Sie studiert?	textarea	character	0	education_level.indexOf(‘uni’) > -1 \|\| occupational_status.indexOf(‘student’) > -1 //js_only		13	232	0.8602	781	0	3	225	2

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	study_major	Was studieren Sie derzeit oder haben Sie studiert?	0	education_level.indexOf(‘uni’) > -1 \|\| occupational_status.indexOf(‘student’) > -1 //js_only		13

Value labels

Response choices
name	value

postal_code

Wie lauten die ersten drei Ziffern ihrer Postleitzahl?

Distribution

Distribution of values for postal_code

21 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
postal_code	Wie lauten die ersten drei Ziffern ihrer Postleitzahl?	text	[0-9][0-9][0-9]	character	0			14	21	0.9873	423	0	3	3	0

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
text	[0-9][0-9][0-9]	postal_code	Wie lauten die ersten drei Ziffern ihrer Postleitzahl?	0			14

Value labels

Response choices
name	value

religion

Welcher Religion bzw. welcher Weltanschauung sind Sie zugehörig?

Distribution

Distribution of values for religion

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_one	religion	Welcher Religion bzw. welcher Weltanschauung sind Sie zugehörig?	0			15

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4
5	5
6	6
7	7

religiosity

Für wie religiös halten Sie sich?

Distribution

Distribution of values for religiosity

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,6,1	religiosity	Für wie religiös halten Sie sich?	0			16

Value labels

Response choices
name	value
1: nicht religiös	1
2	2
3	3
4	4
5	5
6: religiös	6
Item was never rendered for this user.	NA

sex_orientation

Was beschreibt am besten Ihre sexuelle Orientierung?

Distribution

Distribution of values for sex_orientation

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc_button	sex_orientation	Was beschreibt am besten Ihre sexuelle Orientierung?	0	mc_vertical			17

Value labels

Response choices
name	value
Ausschließlich heterosexuell	1
Überwiegend heterosexuell, nur gelegentlich homosexuell	2
Überwiegend heterosexuell, aber mehr als gelegentlich homosexuell	3
Gleichermaßen heterosexuell wie homosexuell	4
Überwiegend homosexuell, aber mehr als gelegentlich heterosexuell	5
Überwiegend homosexuell, nur gelegentlich heterosexuell	6
Ausschließlich homosexuell	7
Asexuell oder aromantisch	8
Item was never rendered for this user.	NA

sex_orientation_special

Wenn Ihnen die obigen Kategorien nicht ausreichen, können Sie es hier in Ihre eigenen Worte fassen.

Distribution

Distribution of values for sex_orientation_special

1577 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
sex_orientation_special	Wenn Ihnen die obigen Kategorien nicht ausreichen, können Sie es hier in Ihre eigenen Worte fassen.	textarea	character	1			18	1577	0.05	83	0	1	557	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	sex_orientation_special	Wenn Ihnen die obigen Kategorien nicht ausreichen, können Sie es hier in Ihre eigenen Worte fassen.	1			18

Value labels

Response choices
name	value

relationship_status

Welchen Beziehungsstatus haben Sie?

Distribution

Distribution of values for relationship_status

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc	relationship_status	Welchen Beziehungsstatus haben Sie?	0	mc_vertical			19

Value labels

Response choices
name	value
Single	1
lose Beziehung	2
feste Partnerschaft	3
verlobt	4
verheiratet	5
andere	6
Item was never rendered for this user.	NA

relationship_count

Sind Sie …

Distribution

Distribution of values for relationship_count

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for relationship_count

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc	relationship_count	Sind Sie …	0	mc_vertical	relationship_status > 1		20

Value labels

Response choices
name	value
monogam (ein Partner)	1
polyamor (mehrere Partner)	2
in einer offenen Beziehung	3
andere	4
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

relationship_details

Sie haben eine Beziehungsform angegeben, die in unserem Fragebogen vielleicht nicht gut erfasst wird. Bitte beschreiben Sie hier Ihre Beziehungsform einfach frei.

Distribution

Distribution of values for relationship_details

1632 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
relationship_details	Sie haben eine Beziehungsform angegeben, die in unserem Fragebogen vielleicht nicht gut erfasst wird. Bitte beschreiben Sie hier Ihre Beziehungsform einfach frei.	textarea	character	1	relationship_status > 5 \| relationship_count > 3		21	1632	0.0169	28	0	16	444	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	relationship_details	Sie haben eine Beziehungsform angegeben, die in unserem Fragebogen vielleicht nicht gut erfasst wird. Bitte beschreiben Sie hier Ihre Beziehungsform einfach frei.	1	relationship_status > 5 \| relationship_count > 3		21

Value labels

Response choices
name	value

duration_relationship_years

Jahre

Distribution

Distribution of values for duration_relationship_years

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for duration_relationship_years

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,100	duration_relationship_years	Jahre	0	relationship_status > 1		24

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

duration_relationship_month

Monate

Distribution

Distribution of values for duration_relationship_month

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for duration_relationship_month

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,12	duration_relationship_month	Monate	0	relationship_status > 1		25

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_gender

Welches Geschlecht hat Ihr Partner?

Distribution

Distribution of values for partner_gender

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_gender

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	partner_gender	Welches Geschlecht hat Ihr Partner?	0	relationship_status > 1		26

Value labels

Response choices
name	value
weiblich	1
männlich	2
anderes	3
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_gender_other

anderes:

Distribution

## Error in if (stats::median(table(x)) == 1) {: missing value where TRUE/FALSE needed

## No non-missing values to show.

1660 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	whitespace
partner_gender_other	anderes:	text	character	1	partner_gender == 3		27	1660	0	0	0	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	partner_gender_other	anderes:	1	partner_gender == 3		27

Value labels

Response choices
name	value

age_partner

Wie alt ist Ihr Partner?

Distribution

Distribution of values for age_partner

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for age_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	14,120,1	age_partner	Wie alt ist Ihr Partner?	0	relationship_status > 1		28

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

abode_with_partner

Wohnen Sie mit Ihrem Partner zusammen?

Distribution

Distribution of values for abode_with_partner

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for abode_with_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		abode_with_partner	Wohnen Sie mit Ihrem Partner zusammen?	0	relationship_status > 1		29

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

abode_flat_share

Wohnen Sie in einer Wohngemeinschaft (abgesehen von Partner)?

Distribution

Distribution of values for abode_flat_share

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	abode_flat_share	Wohnen Sie in einer Wohngemeinschaft (abgesehen von Partner)?	0			30

Value labels

Response choices
name	value
nein	1
mit Eltern/Großeltern	2
ja	3
Item was never rendered for this user.	NA

abode_flat_share_description

Mit wem wohnen Sie zusammen?

Nutzen Sie bitte dieses offene Feld, um uns Angaben über Ihre Mitbewohner zu machen. Am einfachsten ist es für uns, wenn Sie einfach Geschlecht, Alter und gegebenenfalls Verwandtschaftsstatus angeben, bspw. so:

w,55,Mutter w,26,Schwester m,30,Bruder

Sich selbst und Ihren Partner (ggf.) müssen Sie nicht extra nennen.

Distribution

Distribution of values for abode_flat_share_description

898 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
abode_flat_share_description	Mit wem wohnen Sie zusammen? Nutzen Sie bitte dieses offene Feld, um uns Angaben über Ihre Mitbewohner zu machen. Am einfachsten ist es für uns, wenn Sie einfach Geschlecht, Alter und gegebenenfalls Verwandtschaftsstatus angeben, bspw. so: w,55,Mutter w,26,Schwester m,30,Bruder Sich selbst und Ihren Partner (ggf.) müssen Sie nicht extra nennen.	textarea	character	0	abode_flat_share > 1		31	898	0.459	737	0	4	411	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	abode_flat_share_description	Mit wem wohnen Sie zusammen? Nutzen Sie bitte dieses offene Feld, um uns Angaben über Ihre Mitbewohner zu machen. Am einfachsten ist es für uns, wenn Sie einfach Geschlecht, Alter und gegebenenfalls Verwandtschaftsstatus angeben, bspw. so: `w,55,Mutter w,26,Schwester m,30,Bruder` Sich selbst und Ihren Partner (ggf.) müssen Sie nicht extra nennen.	0	abode_flat_share > 1		31

Value labels

Response choices
name	value

abode_alone

Wohnen Sie also alleine?

Distribution

Distribution of values for abode_alone

1455 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for abode_alone

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		abode_alone	Wohnen Sie also alleine?	0	abode_flat_share == 1 & abode_with_partner == 0		32

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

abode_special_case_description

Bitte beschreiben Sie Ihre aktuelle Wohnsituation etwas ausführlicher.

Distribution

Distribution of values for abode_special_case_description

1643 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
abode_special_case_description	Bitte beschreiben Sie Ihre aktuelle Wohnsituation etwas ausführlicher.	textarea	character	0	abode_alone == 0		33	1643	0.0102	17	0	7	177	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	abode_special_case_description	Bitte beschreiben Sie Ihre aktuelle Wohnsituation etwas ausführlicher.	0	abode_alone == 0		33

Value labels

Response choices
name	value

long_distance_relationship

Haben Sie eine Fernbeziehung?

Distribution

Distribution of values for long_distance_relationship

1057 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for long_distance_relationship

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		long_distance_relationship	Haben Sie eine Fernbeziehung?	0	abode_with_partner == 0		34

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

distance_partner

Wie weit wohnen Sie von Ihrem Partner entfernt?

Distribution

Distribution of values for distance_partner

1397 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for distance_partner

Item

Item options
type	name	label	optional	showif	value	item_order
mc	distance_partner	Wie weit wohnen Sie von Ihrem Partner entfernt?	0	long_distance_relationship == 1		35

Value labels

Response choices
name	value
< 1 Std.	1
1 - 2 Std.	2
2-3 Std.	3
3 - 5 Std.	4
5 - 9 Std.	5
9 - 12 Std.	6
&gt; 12 Std.	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

days_same_place_partner_monthly

Wie viele Tage verbringen Sie im Monat an demselben Ort wie Ihr Partner?

Distribution

Distribution of values for days_same_place_partner_monthly

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for days_same_place_partner_monthly

Item

Item options
type	name	label	optional	showif	value	item_order
mc	days_same_place_partner_monthly	Wie viele Tage verbringen Sie im Monat an demselben Ort wie Ihr Partner?	0	relationship_status > 1		36

Value labels

Response choices
name	value
< 3 Tage	1
3 - 4 Tage	2
5 - 6 Tage	3
7 - 14 Tage	4
14-21 Tage	5
21-29 Tage	6
&gt; 29 Tage	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

days_with_partner

Wie viele Tage pro Woche verbringen Sie durchschnittlich an demselben Ort wie ihr Partner?

Distribution

Distribution of values for days_with_partner

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for days_with_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	0,7,1	days_with_partner	Wie viele Tage pro Woche verbringen Sie durchschnittlich an demselben Ort wie ihr Partner?	0	relationship_status > 1		37

Value labels

Response choices
name	value
0: Tage	0
1	1
2	2
3	3
4	4
5	5
6	6
7: Tage	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

nights_with_partner

Wie viele Nächte pro Woche verbringen Sie durchschnittlich mit Ihrem Partner?

Distribution

Distribution of values for nights_with_partner

549 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for nights_with_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	0,7,1	nights_with_partner	Wie viele Nächte pro Woche verbringen Sie durchschnittlich mit Ihrem Partner?	0	relationship_status > 1		38

Value labels

Response choices
name	value
0: Nächte	0
1	1
2	2
3	3
4	4
5	5
6	6
7: Nächte	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

has_children

Haben Sie Kinder?

Distribution

Distribution of values for has_children

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		has_children	Haben Sie Kinder?	0			39

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

nr_children

Wieviele leibliche Kinder haben Sie?

Distribution

Distribution of values for nr_children

1482 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for nr_children

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,20,1	nr_children	Wieviele leibliche Kinder haben Sie?	0	has_children == 1		40

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_father

Ist Ihr aktueller Partner der Vater Ihrer Kinder?

Distribution

Distribution of values for partner_father

1482 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_father

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		partner_father	Ist Ihr aktueller Partner der Vater Ihrer Kinder?	0	has_children == 1		41

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

family_description_optional

Hier können Sie andere Angaben zu Ihren Familienverhältnissen, die in unseren Fragebogen sonst nicht passen, ergänzen (bspw. Adoptivkinder).

Distribution

Distribution of values for family_description_optional

1628 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
family_description_optional	Hier können Sie andere Angaben zu Ihren Familienverhältnissen, die in unseren Fragebogen sonst nicht passen, ergänzen (bspw. Adoptivkinder).	textarea	character	1	has_children == 1		42	1628	0.0193	32	0	13	304	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	family_description_optional	Hier können Sie andere Angaben zu Ihren Familienverhältnissen, die in unseren Fragebogen sonst nicht passen, ergänzen (bspw. Adoptivkinder).	1	has_children == 1		42

Value labels

Response choices
name	value

pregnant

Sind Sie aktuell schwanger oder waren Sie es in den letzten drei Monaten?

Distribution

Distribution of values for pregnant

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		pregnant	Sind Sie aktuell schwanger oder waren Sie es in den letzten drei Monaten?	0			43

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

breast_feeding

Stillen Sie aktuell oder haben Sie in den letzten drei Monaten gestillt?

Distribution

Distribution of values for breast_feeding

21 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		breast_feeding	Stillen Sie aktuell oder haben Sie in den letzten drei Monaten gestillt?	0			44

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

pregnant_stress

Wenn Sie heute erfahren würden, dass Sie schwanger sind, fänden Sie das…

Distribution

Distribution of values for pregnant_stress

59 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for pregnant_stress

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,6,1	pregnant_stress	Wenn Sie heute erfahren würden, dass Sie schwanger sind, fänden Sie das…	0	pregnant == 0		47

Value labels

Response choices
name	value
1: sehr belastend	1
2	2
3	3
4	4
5	5
6: sehr erfreulich	6
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

pregnant_trying

Versuchen Sie derzeit schwanger zu werden?

Distribution

Distribution of values for pregnant_trying

59 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for pregnant_trying

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,6,1	pregnant_trying	Versuchen Sie derzeit schwanger zu werden?	0	pregnant == 0		48

Value labels

Response choices
name	value
1: versuche es zu vermeiden	1
2	2
3	3
4	4
5	5
6: versuche schwanger zu werden	6
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

wish_for_children

Warum nicht?

Distribution

Distribution of values for wish_for_children

120 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		wish_for_children	Warum nicht?	0	mc_vertical left100	pregnant_trying < 4		49

Value labels

Response choices
name	value
1	not_actively_trying
2	not_in_current_life_situation
3	not_with_this_partner
4	dont_have_partner
5	partner_doesnt_want
6	rather_adopt
7	cant_imagine_having_kids

contraception_at_all

Verhüten Sie üblicherweise, wenn Sie Sex haben (Pille, Kondom, Kalendermethode, coitus interruptus, etc.) ?

Distribution

Distribution of values for contraception_at_all

59 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_at_all

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc	contraception_at_all	Verhüten Sie üblicherweise, wenn Sie Sex haben (Pille, Kondom, Kalendermethode, coitus interruptus, etc.) ?	0	mc_vertical	pregnant == 0		51

Value labels

Response choices
name	value
ja	1
meistens	2
ja, aber ich lasse es auch etwas “drauf ankommen”	3
nein, ich lasse es “drauf ankommen”	4
nein, ich habe zur Zeit gar keinen Sex	5
nein, andere Gründe	6
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

contraception_other_reasons_not_to

Hier können Sie andere Gründe, die in unser Fragebogenformat nicht gut passen, angeben

Distribution

Distribution of values for contraception_other_reasons_not_to

1605 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
contraception_other_reasons_not_to	Hier können Sie andere Gründe, die in unser Fragebogenformat nicht gut passen, angeben	textarea	character	0	contraception_at_all == 6		52	1605	0.0331	54	0	5	401	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	contraception_other_reasons_not_to	Hier können Sie andere Gründe, die in unser Fragebogenformat nicht gut passen, angeben	0	contraception_at_all == 6		52

Value labels

Response choices
name	value

contraception_method

Wie verhüten Sie zur Zeit üblicherweise?

Sie können mehrere Methoden angeben.

Distribution

Distribution of values for contraception_method

273 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		contraception_method	Wie verhüten Sie zur Zeit üblicherweise? Sie können mehrere Methoden angeben.	0	mc_vertical	contraception_at_all < 4		53

Value labels

Response choices
name	value
1	hormonal_pill
2	hormonal_other
3	barrier_condoms
4	barrier_other
5	barrier_intrauterine_pessar
6	barrier_coitus_interruptus
7	barrier_no_penetrative_sex
8	awareness_calendar
9	awareness_temperature_billings
10	awareness_computer
11	barrier_spermicide
12	barrier_chemical
13	hormonal_morning_after_pill
14	breast_feeding
15	infertile
16	partner_infertile
17	sterilised
18	partner_sterilised
19	not_listed

contraception_method_other

Welche andere, nicht in der Liste vorkommende, Methode benutzen Sie?

Distribution

Distribution of values for contraception_method_other

1651 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
contraception_method_other	Welche andere, nicht in der Liste vorkommende, Methode benutzen Sie?	text	character	0	contraception_method %contains% ‘not_listed’		54	1651	0.0054	9	0	3	56	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	contraception_method_other	Welche andere, nicht in der Liste vorkommende, Methode benutzen Sie?	0	contraception_method %contains% ‘not_listed’		54

Value labels

Response choices
name	value

contraception_combi

Sie haben angegeben, mehrere Verhütungsmethoden zu kombinieren. Aus welchem Grund, oder welchen Gründen tun Sie das?

Distribution

Distribution of values for contraception_combi

1197 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		contraception_combi	Sie haben angegeben, mehrere Verhütungsmethoden zu kombinieren. Aus welchem Grund, oder welchen Gründen tun Sie das?	0	mc_vertical	contraception_method %contains% “,”		55

Value labels

Response choices
name	value
1	multiple_to_decrease_infection_risk
2	multiple_to_decrease_conception_risk
3	fallback_if_forgotten
4	fallback_if_fertile
5	barrier_if_partner_sick
6	different_methods_for_different_partners
7	other

contraception_method_combination_other

anderer Grund:

Distribution

Distribution of values for contraception_method_combination_other

1636 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
contraception_method_combination_other	anderer Grund:	textarea	character	0	contraception_combi %contains% “other”		56	1636	0.0145	24	0	13	403	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	contraception_method_combination_other	anderer Grund:	0	contraception_combi %contains% “other”		56

Value labels

Response choices
name	value

contraception_calendar_abstinence

Distribution

Distribution of values for contraception_calendar_abstinence

1520 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
contraception_calendar_abstinence	character	1520	0.0843	10	0	8	38	0	NA

contraception_hormonal_pill

Wie heißt Ihre Anti-Baby-Pille?

Falls Sie ein <abbr title=“Eine wirkstoffgleiche Kopie, Nachahmerpräparat, bspw. Dienovel=Valette” class=“hastooltip”>Generikum</abbr> nehmen und es in dieser Liste fehlt, können Sie gerne den Markennamen angeben.

Distribution

Distribution of values for contraception_hormonal_pill

1086 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	median	max	whitespace	n_value_labels
contraception_hormonal_pill	Wie heißt Ihre Anti-Baby-Pille? Falls Sie ein <abbr title=“Eine wirkstoffgleiche Kopie, Nachahmerpräparat, bspw. Dienovel=Valette” class=“hastooltip”>Generikum</abbr> nehmen und es in dieser Liste fehlt, können Sie gerne den Markennamen angeben.	haven_labelled	1086	0.3458	69	0	3	NA	19	0	97

other_pill_name

Sie haben angegeben, dass Ihre Pille in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihrer Pille.

Distribution

Distribution of values for other_pill_name

1581 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
other_pill_name	Sie haben angegeben, dass Ihre Pille in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihrer Pille.	text	character	0	contraception_hormonal_pill == ‘other’		59	1581	0.0476	49	0	5	31	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	other_pill_name	Sie haben angegeben, dass Ihre Pille in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihrer Pille.	0	contraception_hormonal_pill == ‘other’		59

Value labels

Response choices
name	value

contraception_hormonal_other

Welches hormonelle Verhütungsmittel verwenden Sie?

Distribution

Distribution of values for contraception_hormonal_other

1563 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	median	max	whitespace	n_value_labels
contraception_hormonal_other	Welches hormonelle Verhütungsmittel verwenden Sie?	haven_labelled	1563	0.0584	7	0	4	NA	13	0	8

Value labels

Response choices
name	value
1	nuvaring
2	circlet
3	evra
4	mirena
5	depo_provera
6	depo_clinovir
7	implanon
8	other

contraception_hormonal_other_name

Sie haben angegeben, dass Ihr Verhütungsmittel in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihres Verhütungsmittels.

Distribution

Distribution of values for contraception_hormonal_other_name

1634 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	empty	min	max	whitespace
contraception_hormonal_other_name	Sie haben angegeben, dass Ihr Verhütungsmittel in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihres Verhütungsmittels.	text	character	0	contraception_hormonal_other == ‘other’		61	select2hormonal	1634	0.0157	10	0	6	31	0

Item

Item options
type	name	label	optional	class	showif	value	item_order
text	contraception_hormonal_other_name	Sie haben angegeben, dass Ihr Verhütungsmittel in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihres Verhütungsmittels.	0	select2hormonal	contraception_hormonal_other == ‘other’		61

Value labels

Response choices
name	value

contraception_pill_estrogen

Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (µg) Östrogen Ihre Pille enthält. Die meisten Pillen enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.

Distribution

Distribution of values for contraception_pill_estrogen

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_pill_estrogen

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,100,1	contraception_pill_estrogen	Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (µg) Östrogen Ihre Pille enthält. Die meisten Pillen enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.	0	contraception_hormonal_pill == ‘other’		62

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

contraception_pill_gestagen_type

Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, welcher Typ Gestagen verwendet wird.

Distribution

Distribution of values for contraception_pill_gestagen_type

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		contraception_pill_gestagen_type	Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, welcher Typ Gestagen verwendet wird.	0	mc_vertical left500	contraception_hormonal_pill == ‘other’		63

Value labels

Response choices
name	value
1	CMA
2	CPA
3	DNG
4	DSG
5	DSP
6	GSD
7	LYN
8	LNG
9	NEA
10	NES
11	NGT
12	other_gestagen

contraception_pill_gestagen

Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (µg) des jeweiligen Gestagens Ihre Pille enthält. Die meisten Pillen enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.

Distribution

Distribution of values for contraception_pill_gestagen

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_pill_gestagen

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,4000,1	contraception_pill_gestagen	Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (µg) des jeweiligen Gestagens Ihre Pille enthält. Die meisten Pillen enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.	0	contraception_hormonal_pill == ‘other’		64

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

contraception_other_estrogen

Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (µg) Östrogen Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.

Distribution

Distribution of values for contraception_other_estrogen

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_other_estrogen

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,100,1	contraception_other_estrogen	Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (µg) Östrogen Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.	0	contraception_hormonal_pill == ‘other’		65

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

contraception_other_gestagen_type

Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, welcher Typ Gestagen verwendet wird.

Distribution

Distribution of values for contraception_other_gestagen_type

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		contraception_other_gestagen_type	Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, welcher Typ Gestagen verwendet wird.	0	mc_vertical left500	contraception_hormonal_pill == ‘other’		66

Value labels

Response choices
name	value
1	CMA
2	CPA
3	DNG
4	DSG
5	DSP
6	GSD
7	LYN
8	LNG
9	NEA
10	NES
11	NGT
12	other_gestagen

contraception_other_gestagen

Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (µg) des jeweiligen Gestagens Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.

Distribution

Distribution of values for contraception_other_gestagen

1581 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_other_gestagen

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,4000,1	contraception_other_gestagen	Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (µg) des jeweiligen Gestagens Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (µg) zu erhalten.	0	contraception_hormonal_pill == ‘other’		67

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

contraception_app

Benutzen Sie eine Zyklus-App?

Distribution

Distribution of values for contraception_app

36 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		contraception_app	Benutzen Sie eine Zyklus-App?	0			68

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

contraception_app_name

Wie heißt diese App?

Distribution

Distribution of values for contraception_app_name

1249 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
contraception_app_name	Wie heißt diese App?	text	character	0	contraception_app == 1		69	1249	0.2476	173	0	3	91	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	contraception_app_name	Wie heißt diese App?	0	contraception_app == 1		69

Value labels

Response choices
name	value

hormonal_contraception_last3m

Haben Sie in den letzten drei Monaten hormonell verhütet?

Distribution

Distribution of values for hormonal_contraception_last3m

36 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		hormonal_contraception_last3m	Haben Sie in den letzten drei Monaten hormonell verhütet?	0			70

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

contraception_meeting_partner

Haben Sie hormonell verhütet (z.B. Pille), als Sie Ihren Partner kennengelernt haben?

Distribution

Distribution of values for contraception_meeting_partner

560 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for contraception_meeting_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		contraception_meeting_partner	Haben Sie hormonell verhütet (z.B. Pille), als Sie Ihren Partner kennengelernt haben?	0	relationship_status > 1		71

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

self_rated_health

Bitte beurteilen Sie Ihren allgemeinen Gesundheitszustand zum jetzigen Zeitpunkt.

Distribution

Distribution of values for self_rated_health

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc	self_rated_health	Bitte beurteilen Sie Ihren allgemeinen Gesundheitszustand zum jetzigen Zeitpunkt.	0			75

Value labels

Response choices
name	value
sehr gut	1
gut	2
teils gut/teils schlecht	3
schlecht	4
sehr schlecht	5
Item was never rendered for this user.	NA

height

Bitte geben Sie Ihre Körpergröße in cm an (ohne Schuhe).

Distribution

Distribution of values for height

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	80,230	height	Bitte geben Sie Ihre Körpergröße in cm an (ohne Schuhe).	0			76

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

weight

Bitte geben Sie Ihr Gewicht in kg an (ohne Kleidung).

Distribution

Distribution of values for weight

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	40,200	weight	Bitte geben Sie Ihr Gewicht in kg an (ohne Kleidung).	0			77

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

hormonal_med

Haben Sie in den letzten 3 Monaten hormonelle Medikamente (außer Verhütung) genommen?

Distribution

Distribution of values for hormonal_med

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		hormonal_med	Haben Sie in den letzten 3 Monaten hormonelle Medikamente (außer Verhütung) genommen?	0			78

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

hormonal_med_name

Welche?

Distribution

Distribution of values for hormonal_med_name

1548 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_multiple	hormonal_med_name	Welche?	0	hormonal_med == 1		79

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4

psychoactive_med

Nehmen Sie psychoaktive Medikamente (z. B. gegen Depression)?

Distribution

Distribution of values for psychoactive_med

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		psychoactive_med	Nehmen Sie psychoaktive Medikamente (z. B. gegen Depression)?	0			80

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

psychoactive_med_name

Welche?

Distribution

Distribution of values for psychoactive_med_name

1605 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
psychoactive_med_name	Welche?	text	character	0	psychoactive_med ==1		81	1605	0.0331	44	0	5	51	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	psychoactive_med_name	Welche?	0	psychoactive_med ==1		81

Value labels

Response choices
name	value

alcohol_weekly

Wie viel Gläser Alkohol trinken Sie im Schnitt in der Woche?

Distribution

Distribution of values for alcohol_weekly

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,50, 0.5	alcohol_weekly	Wie viel Gläser Alkohol trinken Sie im Schnitt in der Woche?	0			82

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

cigarettes_daily

Wie viele Zigaretten rauchen Sie im Schnitt am Tag?

Distribution

Distribution of values for cigarettes_daily

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,100,1	cigarettes_daily	Wie viele Zigaretten rauchen Sie im Schnitt am Tag?	0			83

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

sport_weekly

Wie viele Stunden pro Woche treiben Sie schweißtreibenden Sport?

Distribution

Distribution of values for sport_weekly

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,60,0.5	sport_weekly	Wie viele Stunden pro Woche treiben Sie schweißtreibenden Sport?	0			84

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

sport_kinds

Wenn Sie Sport treiben – welche Sportarten sind dies typischerweise? Wählen Sie aus der Liste der vorgeschlagenen Sportarten aus und/oder fügen Sie „Ihre“ Sportart(en) hinzu. Sie können mehrere Sportarten angeben oder auch gar keine.

Distribution

Distribution of values for sport_kinds

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_multiple	sport_kinds	Wenn Sie Sport treiben – welche Sportarten sind dies typischerweise? <small><em>Wählen Sie aus der Liste der vorgeschlagenen Sportarten aus und/oder fügen Sie „Ihre“ Sportart(en) hinzu. Sie können mehrere Sportarten angeben oder auch gar keine.</em></small>	0			85

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4
5	5
6	6
7	7

meat_eating

Essen Sie Fleisch und tierische Produkte?

Distribution

Distribution of values for meat_eating

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		meat_eating	Essen Sie Fleisch und tierische Produkte?	0			86

Value labels

Response choices
name	value
1	1_every_day
2	2_frequently
3	3_rarely
4	4_only_poultry
5	5_only_fish
6	6_vegetarian
7	7_vegan

menarche

Wie alt waren Sie, als Sie Ihre erste Monatsblutung (Periode, Tage, Menstruation) hatten?

Distribution

Distribution of values for menarche

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	8,20	menarche	Wie alt waren Sie, als Sie Ihre erste Monatsblutung (Periode, Tage, Menstruation) hatten?	0			87

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

menarche_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for menarche_certainty

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menarche_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0			88

Value labels

Response choices
name	value
stimmt genau	1
±0.5 Jahre	2
±1 Jahr	3
±2 Jahre	4
±3 Jahre	5
±4 Jahre	6
unsicherer	7
Item was never rendered for this user.	NA

number_sexual_partner

Mit wie vielen Personen haben Sie insgesamt in Ihrem Leben Geschlechtsverkehr gehabt?

Distribution

Distribution of values for number_sexual_partner

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,400	number_sexual_partner	Mit wie vielen Personen haben Sie insgesamt in Ihrem Leben Geschlechtsverkehr gehabt?	0			89

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

number_sexual_partner_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for number_sexual_partner_certainty

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	number_sexual_partner_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0			90

Value labels

Response choices
name	value
stimmt genau	1
±1	2
±2	3
±3	4
±5	5
±10	6
±20	7
unsicherer	8
Item was never rendered for this user.	NA

first_time

Wie alt waren Sie, als Sie das erste Mal Geschlechtsverkehr hatten?

Distribution

Distribution of values for first_time

134 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for first_time

Item

Item options
type	name	label	optional	showif	value	item_order
number	first_time	Wie alt waren Sie, als Sie das erste Mal Geschlechtsverkehr hatten?	0	number_sexual_partner > 0		91

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

first_time_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for first_time_certainty

134 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for first_time_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	first_time_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0	number_sexual_partner > 0		92

Value labels

Response choices
name	value
stimmt genau	1
±0.5 Jahre	2
±1 Jahr	3
±2 Jahre	4
±3 Jahre	5
±4 Jahre	6
unsicherer	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

mother_menopause_yes

Hat Ihre Mutter die Menopause erreicht?

Distribution

Distribution of values for mother_menopause_yes

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	mother_menopause_yes	Hat Ihre Mutter die Menopause erreicht?	0			93

Value labels

Response choices
name	value
Ja	1
Nein, ist zur Zeit in den Wechseljahren	2
Nein, noch nicht	3
Nein, vorher verstorben	4
Item was never rendered for this user.	NA

mother_menopause_age

Wie alt war Ihre Mutter beim Einsetzen ihrer Menopause?

Wenn Sie es den Zeitpunkt nicht genau benennen können, versuchen Sie sich zu erinnern, wann Ihre Mutter über typische Begleiterscheinungen (z.B. Hitzewallungen, etc.) gesprochen hat. Idealerweise fragen Sie Ihre Mutter kurz (telefonisch), aber Sie können auch fortfahren, ohne dies zu tun, wenn es grade nicht geht.

Distribution

Distribution of values for mother_menopause_age

895 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for mother_menopause_age

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	30,60	mother_menopause_age	Wie alt war Ihre Mutter beim Einsetzen ihrer Menopause? Wenn Sie es den Zeitpunkt nicht genau benennen können, versuchen Sie sich zu erinnern, wann Ihre Mutter über typische Begleiterscheinungen (z.B. Hitzewallungen, etc.) gesprochen hat. Idealerweise fragen Sie Ihre Mutter kurz (telefonisch), aber Sie können auch fortfahren, ohne dies zu tun, wenn es grade nicht geht.	0	mother_menopause_yes == 1		94

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

mother_menopause_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for mother_menopause_certainty

895 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for mother_menopause_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	mother_menopause_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0	mother_menopause_yes == 1		95

Value labels

Response choices
name	value
stimmt genau <small>(ich habe sie gefragt)</small>	1
±0.5 Jahre	2
±1 Jahr	3
±2 Jahre	4
±3 Jahre	5
±4 Jahre	6
unsicherer <small>(ich habe geraten)</small>	7
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menopause_yes

Ist bei Ihnen selbst die Menopause eingetreten?

Distribution

Distribution of values for menopause_yes

1597 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menopause_yes

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menopause_yes	Ist bei Ihnen selbst die Menopause eingetreten?	0	age > 43		96

Value labels

Response choices
name	value
Ja	1
Nein, bin zur Zeit in den Wechseljahren	2
Nein, noch nicht	3
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menopause_age

Wie alt waren Sie selbst zum Eintritt Ihrer Menopause?

Distribution

Distribution of values for menopause_age

1637 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menopause_age

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	30,60	menopause_age	Wie alt waren Sie selbst zum Eintritt Ihrer Menopause?	0	menopause_yes == 1		97

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menopause_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for menopause_certainty

1637 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menopause_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menopause_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0	menopause_yes == 1		98

Value labels

Response choices
name	value
stimmt genau	1
±0.5 Jahre	2
±1 Jahr	3
±2 Jahre	4
±3 Jahre	5
±4 Jahre	6
±7 Jahre	7
unsicherer	8
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menstruation_regular

Haben Sie zur Zeit regelmäßig (ungefähr monatlich) Ihre Periode?

Distribution

Distribution of values for menstruation_regular

53 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc_button		menstruation_regular	Haben Sie zur Zeit regelmäßig (ungefähr monatlich) Ihre Periode?	0			99

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

menstruation_last

Nennen Sie bitte den ersten Tag (Start) Ihrer letzten Periode (Menstruationsblutung). Wenn möglich schauen Sie das Datum bitte in Ihrem Kalender nach.

Distribution

## 246  unique, categorical values, so not shown.

355 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	min	median	max
menstruation_last	Nennen Sie bitte den ersten Tag (Start) Ihrer letzten Periode (Menstruationsblutung). Wenn möglich schauen Sie das Datum bitte in Ihrem Kalender nach.	date	-2months,today	Date	0	menstruation_regular == 1		100	355	0.7861	246	2016-04-01	2016-08-30	2017-01-08

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
date	-2months,today	menstruation_last	Nennen Sie bitte den ersten Tag (Start) Ihrer letzten Periode (Menstruationsblutung). Wenn möglich schauen Sie das Datum bitte in Ihrem Kalender nach.	0	menstruation_regular == 1		100

Value labels

Response choices
name	value

menstruation_last_certainty

Wie sicher sind Sie bei dieser Angabe?

Distribution

Distribution of values for menstruation_last_certainty

355 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menstruation_last_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menstruation_last_certainty	Wie sicher sind Sie bei dieser Angabe?	0	menstruation_regular == 1		101

Value labels

Response choices
name	value
stimmt genau	1
±1 Tag	2
±2 Tage	3
±3 Tage	4
±4 Tage	5
±5 Tage	6
±6 Tage	7
unsicherer	8
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menstruation_length

Wie lange dauert Ihr Menstruationszyklus (Tage vom Beginn einer Monatsblutung bis zum Beginn der nächsten Monatsblutung; meist zwischen 25-35 Tagen)?

Distribution

Distribution of values for menstruation_length

355 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menstruation_length

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	15,50,1	menstruation_length	Wie lange dauert Ihr Menstruationszyklus (Tage vom Beginn einer Monatsblutung bis zum Beginn der nächsten Monatsblutung; meist zwischen 25-35 Tagen)?	0	menstruation_regular == 1		102

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menstruation_length_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for menstruation_length_certainty

355 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menstruation_length_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menstruation_length_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0	menstruation_regular == 1		103

Value labels

Response choices
name	value
stimmt genau	1
±1 Tag	2
±2 Tage	3
±3 Tage	4
±4 Tage	5
±5 Tage	6
±6 Tage	7
unsicherer	8
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menstruation_regularity

Wie regelmäßig war in den letzten 3 Monaten Ihr Menstruationszyklus?

Distribution

Distribution of values for menstruation_regularity

355 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menstruation_regularity

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc	menstruation_regularity	Wie regelmäßig war in den letzten 3 Monaten Ihr Menstruationszyklus?	0	mc_vertical	menstruation_regular == 1		104

Value labels

Response choices
name	value
Völlig (gar keine Schwankungen)	1
Sehr (max. 1-2 Tage Schwankungen)	2
Etwas (3-5 Tage Schwankungen)	3
Kaum (über 5 Tage Schwankungen)	4
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

menstruation_regularity_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for menstruation_regularity_certainty

355 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for menstruation_regularity_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	menstruation_regularity_certainty	Wie sicher sind Sie sich bei dieser Angabe?	0	menstruation_regular == 1		105

Value labels

Response choices
name	value
stimmt genau	1
±1 Tag	2
±2 Tage	3
±3 Tage	4
±4 Tage	5
±5 Tage	6
±6 Tage	7
unsicherer	8
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

free_not_covered

Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an. optional

Distribution

Distribution of values for free_not_covered

1471 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
free_not_covered	Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an. <small>optional</small>	textarea	character	1			107	1471	0.1139	189	0	1	1002	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	free_not_covered	Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an. <small>optional</small>	1			107

Value labels

Response choices
name	value

hetero_relationship

Distribution

Distribution of values for hetero_relationship

36 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
hetero_relationship	numeric	36	0.9783	0	1	1	0.6718	0.4697	▃▁▁▁▇	NA

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	1660	0	7	7	0	NA

ended_date

user finished survey

Distribution

## 215  unique, categorical values, so not shown.

53 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
ended_date	user finished survey	Date	53	0.9681	215	2016-05-02	2016-09-15	2017-01-14

contraception_other_pill_estrogen

Distribution

Distribution of values for contraception_other_pill_estrogen

1588 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
contraception_other_pill_estrogen	numeric	1588	0.0434	20	2700	2700	1480	1337	▆▁▁▁▇	NA

contraception_other_pill_gestagen

Distribution

Distribution of values for contraception_other_pill_gestagen

1557 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
contraception_other_pill_gestagen	numeric	1557	0.062	75	11700	150000	22694	30969	▇▂▁▁▁	NA

contraception_other_pill_gestagen_type

Distribution

Distribution of values for contraception_other_pill_gestagen_type

1557 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
contraception_other_pill_gestagen_type	character	1557	0.062	6	0	9	25	0	NA

hormonal_contraception

Distribution

Distribution of values for hormonal_contraception

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
hormonal_contraception	logical	0	1	FAL: 982, TRU: 678	0.4084	NA

contraception_method_broad

Distribution

Distribution of values for contraception_method_broad

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
contraception_method_broad	character	0	1	7	273	0	10	0	NA

contraception_hormonal_pill_estrogen

Distribution

Distribution of values for contraception_hormonal_pill_estrogen

1127 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
contraception_hormonal_pill_estrogen	numeric	1127	0.3211	0	30	100	27.23	8.007	▃▇▁▁▁	NA

contraception_hormonal_pill_gestagen_type

Distribution

Distribution of values for contraception_hormonal_pill_gestagen_type

1086 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
contraception_hormonal_pill_gestagen_type	character	1086	0.3458	12	79	0	14	0	NA

estrogen_progestogen

Distribution

Distribution of values for estrogen_progestogen

8 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
estrogen_progestogen	character	8	0.9952	3	0	12	24	0	NA

living_situation

Distribution

Distribution of values for living_situation

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
living_situation	character	0	1	7	0	5	13	0	NA

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "s1_demo",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=1660 rows and 114 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "created", "modified", "ended", "expired", "info_study", "lab_code", "age", "gender", "gender_other", "education_years", "education_level", "education_level_special", "occupational_status", "occupation", "net_income", "study_major", "postal_code", "religion", "religiosity", "sex_orientation", "sex_orientation_special", "relationship_status", "relationship_count", "relationship_details", "duration_relationship_years", "duration_relationship_month", "partner_gender", "partner_gender_other", "age_partner", "abode_with_partner", "abode_flat_share", "abode_flat_share_description", "abode_alone", "abode_special_case_description", "long_distance_relationship", "distance_partner", "days_same_place_partner_monthly", "days_with_partner", "nights_with_partner", "has_children", "nr_children", "partner_father", "family_description_optional", "pregnant", "breast_feeding", "pregnant_stress", "pregnant_trying", "wish_for_children", "contraception_at_all", "contraception_other_reasons_not_to", "contraception_method", "contraception_method_other", "contraception_combi", "contraception_method_combination_other", "contraception_calendar_abstinence", "contraception_hormonal_pill", "other_pill_name", "contraception_hormonal_other", "contraception_hormonal_other_name", "contraception_pill_estrogen", "contraception_pill_gestagen_type", "contraception_pill_gestagen", "contraception_other_estrogen", "contraception_other_gestagen_type", "contraception_other_gestagen", "contraception_app", "contraception_app_name", "hormonal_contraception_last3m", "contraception_meeting_partner", "self_rated_health", "height", "weight", "hormonal_med", "hormonal_med_name", "psychoactive_med", "psychoactive_med_name", "alcohol_weekly", "cigarettes_daily", "sport_weekly", "sport_kinds", "meat_eating", "menarche", "menarche_certainty", "number_sexual_partner", "number_sexual_partner_certainty", "first_time", "first_time_certainty", "mother_menopause_yes", "mother_menopause_age", "mother_menopause_certainty", "menopause_yes", "menopause_age", "menopause_certainty", "menstruation_regular", "menstruation_last", "menstruation_last_certainty", "menstruation_length", "menstruation_length_certainty", "menstruation_regularity", "menstruation_regularity_certainty", "free_not_covered", "hetero_relationship", "short", "ended_date", "contraception_other_pill_estrogen", "contraception_other_pill_gestagen", "contraception_other_pill_gestagen_type", "hormonal_contraception", "contraception_method_broad", "contraception_hormonal_pill_estrogen", "contraception_hormonal_pill_gestagen_type", "estrogen_progestogen", "living_situation"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "info_study",
      "description": "Wie sind Sie auf unsere Studie aufmerksam geworden?",
      "value": "1. Einladung durch das Studienteam,\n2. Aushänge Georg-August-Universität Göttingen,\n3. Privater Kontakt,\n4. www.psytests.de,\n5. Medien,\n6. andere",
      "maxValue": "6",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "lab_code",
      "description": "Nehmen Sie auch an unserer Laborstudie _Attraktivitätsbeurteilungen_ in Göttingen teil und haben einen Code für diese Studie erhalten? \nWenn ja, geben Sie bitte hier unbedingt Ihren persönlichen Code ein.\nWenn nein, lassen Sie dieses Feld einfach aus.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "age",
      "description": "Ihr Alter",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "gender",
      "description": "Ihr Geschlecht",
      "value": "1. weiblich,\n2. anderes,\nNA. Item was never rendered for this user.",
      "maxValue": 2,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "gender_other",
      "description": "anderes:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "education_years",
      "description": "Wie viele Bildungsjahre (Schule, Studium an Universität oder FH, Jahre als Doktorand/in, NICHT Berufsschule etc.)                                                                                                                        haben Sie hinter sich?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "education_level",
      "description": "Was ist ihr höchster, bislang erreichter Bildungsgrad",
      "value": "0_not_finished. ohne Schulabschluss,\n1_hauptschule. Hauptschulabschluss,\n2_realschule. Realschulabschluss,\n3_polytechnic. Abschluss der polytechnischen Oberschule,\n4_professional_school. Berufsschulabschluss,\n5_fachabitur. Fachhochschulreife,\n6_abitur. Hochschulreife,\n7_vocational_uni_bachelor. Fachhochschulabschluss Bachelor,\n8_uni_bachelor. Hochschulabschluss Bachelor,\n9_vocational_uni_master_level. Fachhochschulabschluss Master/Magister/Diplom,\n10_uni_master_level. Hochschulabschluss Master/Magister/Diplom,\n11_uni_doctorate. Promotion,\n12_uni_habilitation. Habilitation",
      "maxValue": "9_vocational_uni_master_level",
      "minValue": "0_not_finished",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "education_level_special",
      "description": "Haben Sie einen Bildungsgrad, der sich hier nicht gut einsortieren lässt (bspw. Meister)?\nWenn die obige Liste nicht ausreicht, können Sie das hier frei ergänzen.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "occupational_status",
      "description": "Welchen beruflichen Status haben Sie derzeit? ",
      "value": "not_working. nicht berufstätig,\npupil. Schülerin,\ntrainee. Auszubildende,\nstudent. Studentin,\nhomemaker. Haus- und Familienarbeit ,\nemployed. Berufstätig,\nintern. Praktikantin",
      "maxValue": "trainee",
      "minValue": "employed",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "occupation",
      "description": "Welchen Beruf üben Sie aus?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "net_income",
      "description": "Wie viel Geld haben Sie monatlich zur Verfügung (netto)?",
      "value": "euro_lt_500.  < 500€,\neuro_500_1000. 500-1000€,\neuro_1000_2000. 1000-2000€,\neuro_2000_3000. 2000-3000€,\neuro_gt_3000. \\> 3000€,\ndont_tell. möchte ich nicht angeben",
      "maxValue": "euro_lt_500",
      "minValue": "dont_tell",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "study_major",
      "description": "Was studieren Sie derzeit oder haben Sie studiert?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "postal_code",
      "description": "Wie lauten die ersten drei Ziffern ihrer Postleitzahl?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "religion",
      "description": "Welcher Religion bzw. welcher Weltanschauung sind Sie zugehörig? ",
      "value": "1. Christentum ,\n2. Islam,\n3. Buddhismus,\n4. Hinduismus,\n5. Judentum ,\n6. andere ,\n7. nicht gläubig",
      "maxValue": "7",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "religiosity",
      "description": "Für wie religiös halten Sie sich? ",
      "value": "1. 1: nicht religiös,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: religiös,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_orientation",
      "description": "Was beschreibt am besten Ihre sexuelle Orientierung?",
      "value": "1. Ausschließlich heterosexuell,\n2. Überwiegend heterosexuell, nur gelegentlich homosexuell,\n3. Überwiegend heterosexuell, aber mehr als gelegentlich homosexuell,\n4. Gleichermaßen heterosexuell wie homosexuell,\n5. Überwiegend homosexuell, aber mehr als gelegentlich heterosexuell,\n6. Überwiegend homosexuell, nur gelegentlich heterosexuell,\n7. Ausschließlich homosexuell,\n8. Asexuell oder aromantisch,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_orientation_special",
      "description": "Wenn Ihnen die obigen Kategorien nicht ausreichen, können Sie es hier in Ihre eigenen Worte fassen.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_status",
      "description": "Welchen Beziehungsstatus haben Sie?",
      "value": "1. Single,\n2. lose Beziehung,\n3. feste Partnerschaft,\n4. verlobt,\n5. verheiratet,\n6. andere,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_count",
      "description": "Sind Sie ...",
      "value": "1. monogam (ein Partner),\n2. polyamor (mehrere Partner),\n3. in einer offenen Beziehung,\n4. andere,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 4,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_details",
      "description": "Sie haben eine Beziehungsform angegeben, die in unserem Fragebogen vielleicht nicht gut erfasst wird. Bitte beschreiben Sie hier Ihre Beziehungsform einfach frei.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "duration_relationship_years",
      "description": "Jahre",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "duration_relationship_month",
      "description": "Monate",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_gender",
      "description": "Welches Geschlecht hat Ihr Partner?",
      "value": "1. weiblich,\n2. männlich,\n3. anderes,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 3,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_gender_other",
      "description": "anderes:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "age_partner",
      "description": "Wie alt ist Ihr Partner?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "abode_with_partner",
      "description": "Wohnen Sie mit Ihrem Partner zusammen?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "abode_flat_share",
      "description": "Wohnen Sie in einer Wohngemeinschaft (abgesehen von Partner)?",
      "value": "1. nein,\n2. mit Eltern/Großeltern,\n3. ja,\nNA. Item was never rendered for this user.",
      "maxValue": 3,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "abode_flat_share_description",
      "description": "Mit wem wohnen Sie zusammen?\n\nNutzen Sie bitte dieses offene Feld, um uns Angaben über Ihre Mitbewohner zu machen.\nAm einfachsten ist es für uns, wenn Sie einfach Geschlecht, Alter und gegebenenfalls Verwandtschaftsstatus angeben, bspw. so:\n\n     w,55,Mutter\n     w,26,Schwester\n     m,30,Bruder\n\nSich selbst und Ihren Partner (ggf.) müssen Sie nicht extra nennen.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "abode_alone",
      "description": "Wohnen Sie also alleine?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "abode_special_case_description",
      "description": "Bitte beschreiben Sie Ihre aktuelle Wohnsituation etwas ausführlicher.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "long_distance_relationship",
      "description": "Haben Sie eine Fernbeziehung?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "distance_partner",
      "description": "Wie weit wohnen Sie von Ihrem Partner entfernt?",
      "value": "1. < 1 Std.,\n2. 1 - 2 Std.,\n3. 2-3 Std.,\n4. 3 - 5 Std.,\n5. 5 - 9 Std.,\n6. 9 - 12 Std.,\n7. \\> 12 Std.,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "days_same_place_partner_monthly",
      "description": "Wie viele Tage verbringen Sie im Monat  an demselben Ort wie Ihr Partner?",
      "value": "1. < 3 Tage,\n2. 3 - 4 Tage,\n3. 5 - 6 Tage,\n4. 7 - 14 Tage,\n5. 14-21 Tage,\n6. 21-29 Tage,\n7. \\> 29 Tage,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "days_with_partner",
      "description": "Wie viele Tage pro Woche verbringen Sie durchschnittlich an demselben Ort wie ihr Partner?",
      "value": "0. 0: Tage,\n1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: Tage,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "nights_with_partner",
      "description": "Wie viele Nächte pro Woche verbringen Sie durchschnittlich mit Ihrem Partner?",
      "value": "0. 0: Nächte,\n1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: Nächte,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "has_children",
      "description": "Haben Sie Kinder?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "nr_children",
      "description": "Wieviele leibliche Kinder haben Sie?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_father",
      "description": "Ist Ihr aktueller Partner der Vater Ihrer Kinder?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "family_description_optional",
      "description": "Hier können Sie andere Angaben zu Ihren Familienverhältnissen, die in unseren Fragebogen sonst nicht passen, ergänzen (bspw. Adoptivkinder).",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pregnant",
      "description": "Sind Sie aktuell schwanger oder waren Sie es in den letzten drei Monaten?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "breast_feeding",
      "description": "Stillen Sie aktuell oder haben Sie in den letzten drei Monaten gestillt?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pregnant_stress",
      "description": "Wenn Sie heute erfahren würden, dass Sie schwanger sind, fänden Sie das...",
      "value": "1. 1: sehr belastend,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: sehr erfreulich,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pregnant_trying",
      "description": "Versuchen Sie derzeit schwanger zu werden?",
      "value": "1. 1: versuche es zu vermeiden,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: versuche schwanger zu werden,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "wish_for_children",
      "description": "Warum nicht?",
      "value": "not_actively_trying. Ich könnte mir vorstellen, demnächst schwanger zu werden, aber versuche es zur Zeit nicht aktiv.,\nnot_in_current_life_situation. `r ifelse(relationship_status == 1, 'Ich könnte mir vorstellen schwanger zu werden, aber eher nicht in meiner derzeitigen Lebenssituation.', 'Ich könnte mir vorstellen mit meinem aktuellen Partner schwanger zu werden, aber eher nicht in meiner derzeitigen Lebenssituation.')`,\nnot_with_this_partner. `r ifelse(relationship_status == 1, '', 'Ich könnte mir vorstellen schwanger zu werden, aber eher nicht mit meinem aktuellen Partner.')`,\ndont_have_partner. `r ifelse(relationship_status == 1, 'Ich könnte mir vorstellen schwanger zu werden, aber habe keinen Partner, der in Frage käme.', '')`,\npartner_doesnt_want. `r ifelse(relationship_status == 1, '', 'Ich könnte mir vorstellen schwanger zu werden, aber mein Partner möchte das nicht.')`,\nrather_adopt. Ich möchte Kinder, aber möchte eher adoptieren / Pflegekinder aufnehmen.,\ncant_imagine_having_kids. Ich kann mir nicht vorstellen, jemals Kinder zu bekommen.",
      "maxValue": "rather_adopt",
      "minValue": "cant_imagine_having_kids",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_at_all",
      "description": "Verhüten Sie üblicherweise, wenn Sie Sex haben (Pille, Kondom, Kalendermethode, coitus interruptus, etc.) ?",
      "value": "1. ja,\n2. meistens,\n3. ja, aber ich lasse es auch etwas \"drauf ankommen\",\n4. nein, ich lasse es \"drauf ankommen\",\n5. nein, ich habe zur Zeit gar keinen Sex,\n6. nein, andere Gründe,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_reasons_not_to",
      "description": "Hier können Sie andere Gründe, die in unser Fragebogenformat nicht gut passen, angeben",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_method",
      "description": "Wie verhüten Sie zur Zeit üblicherweise?\n\nSie können mehrere Methoden angeben.",
      "value": "hormonal_pill. Orale Kontrazeptiva (Pille),\nhormonal_other. andere hormonelle Verhütung (Depotspritze, Hormonimplantat, Verhütungsring, Verhütungspflaster, Hormonspirale),\nbarrier_condoms. Kondome,\nbarrier_other. Andere Barrieremethoden (Diaphragma, Frauenkondom, Portiokappe),\nbarrier_intrauterine_pessar. Kupferspirale oder -kette (Intrauterinpessar),\nbarrier_coitus_interruptus. Coitus interruptus,\nbarrier_no_penetrative_sex. Verzicht auf penetrativen Geschlechtsverkehr,\nawareness_calendar. Kalendermethode,\nawareness_temperature_billings. Temperatur- / Billings- / Symptothermale Methode,\nawareness_computer. Verhütungscomputer (Persona, LadyComp, Cyclotest, …),\nbarrier_spermicide. Spermizide,\nbarrier_chemical. Chemische Verhütung,\nhormonal_morning_after_pill. \"Pille danach\",\nbreast_feeding. Stillen,\ninfertile. ich bin unfruchtbar,\npartner_infertile. mein Partner ist unfruchtbar,\nsterilised. ich bin sterilisiert,\npartner_sterilised. mein Partner ist sterilisiert,\nnot_listed. Andere",
      "maxValue": "sterilised",
      "minValue": "awareness_calendar",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_method_other",
      "description": "Welche andere, nicht in der Liste vorkommende, Methode benutzen Sie?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_combi",
      "description": "Sie haben angegeben, mehrere Verhütungsmethoden zu kombinieren. Aus welchem Grund, oder welchen Gründen tun Sie das?",
      "value": "multiple_to_decrease_infection_risk. immer mehrere gleichzeitig (Verhütung + sexuelle übertragbare Krankheiten vermeiden),\nmultiple_to_decrease_conception_risk. immer mehrere gleichzeitig (Verhütungssicherheit erhöhen),\nfallback_if_forgotten. falle auf zweite Methode zurück, wenn ich oder mein Partner die erste vergessen habe zu nehmen/ zu kaufen (z.B. Pille + Kondome, oder Kondome + Koitus interruptus),\nfallback_if_fertile. falle auf zweite Methode zurück, wenn ich fruchtbar bin (z.B. Kalendermethode + Kondome oder Koitus interruptus im fruchtbaren Fenster),\nbarrier_if_partner_sick. eine Methode zur Verhütung, andere zur Vermeidung von nicht-sexueller Ansteckung (z.B. Pille + Abstinenz, wenn Geschlechtspartner gerade erkältet),\ndifferent_methods_for_different_partners. eine Methode für bestimmte Partner, andere Methode für andere Partner (z.B. Pille bei Sex mit gut bekannter/vertrauter Person, Kondome bei Sex mit weniger gut bekannter Person),\nother. anderer Grund",
      "maxValue": "other",
      "minValue": "barrier_if_partner_sick",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_method_combination_other",
      "description": "anderer Grund: ",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_calendar_abstinence",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_hormonal_pill",
      "description": "Wie heißt Ihre Anti-Baby-Pille?\n\nFalls Sie ein <abbr title=\"Eine wirkstoffgleiche Kopie, Nachahmerpräparat, bspw. Dienovel=Valette\" class=\"hastooltip\">Generikum<\/abbr> nehmen und es in dieser Liste fehlt, können Sie gerne den Markennamen angeben.",
      "value": "other. Meine Pille kommt in dieser Liste nicht vor.,\n28_mini. 28 mini ,\naida. Aida,\nalessia_hexal. Alessia HEXAL,\nasumate_20. Asumate 20,\nattempta_35. Attempta ratiopharm-35,\nbalanca. Balanca,\nbelara. Belara,\nbellahexal_35. BellaHexal-35,\nbellissima. Bellissima,\nbilmon. Bilmon,\nbiviol. Biviol,\nbonadea. BonaDea,\ncerazette. Cerazette ,\nchariva. Chariva,\nchloee. Chloee,\ncilest. Cilest,\nclevia. Clevia,\nconceplan_m. Conceplan M,\ncyprella. Cyprella ,\ncyproderm. Cyproderm,\ncypronette_al. Cypronette AL,\ndamara. Damara ,\ndaylette. Daylette,\ndesirett. Desirett,\ndesmin_20. Desmin  20,\ndesmin_30. Desmin  30,\ndiamilla. Diamilla,\ndiane_35. Diane-35,\nenriqa. Enriqa,\nergalea. Ergalea,\nestelle. Estelle,\neufem. eufem,\nevaluna_20. Evaluna 20,\nevaluna_30. Evaluna 30,\neve_20. EVE 20,\nfemigoa. Femigoa,\nfemigyne_ratiopharm. Femigyne-ratiopharm,\nfemikadin_20. Femikadin 20,\nfemikadin_30. Femikadin 30,\nfemovan. Femovan,\nfinic. Finic,\ngabrielle. Gabrielle,\ngravistat_125. Gravistat 125,\nillina. Illina,\njennifer. Jennifer,\njubrele. Jubrele ,\njuliane_20. Juliane 20,\njuliane_30. Juliane 30,\njuliette. Juliette,\nlamuna_20. Lamuna20,\nlamuna_30. Lamuna30,\nleios. Leios,\nleonahexal. LeonaHexal,\nlevina. Levina,\nlevomin. Levomin,\nliana. Liana,\nlilia. Lilia,\nlisette. Lisette,\nlovelle. Lovelle,\nmadinette. Madinette,\nmaitalon_20. Maitalon 20,\nmaitalon_30. Maitalon 30,\nmarvelon. Marvelon,\nmaxim. Maxim,\nmayra. mayra,\nmicrogynon. Microgynon,\nmicrolut. Microlut ,\nminette. Minette,\nminisiston. Minisiston,\nminisiston_20_fem. Minisiston 20 fem,\nminulet. Minulet,\nmiranova. Miranova,\nmonahexal. MonaHexal,\nmonostep. MonoStep,\nmorea_sanol. Morea sanol,\nneo_eunomin. Neo-Eunomin,\nnovastep. NovaStep,\nnovial. Novial ,\npetibelle. Petibelle,\npink_luna. Pink Luna,\npramino. Pramino,\nqlaira. Qlaira,\nseculact. Seculact,\nsynphasec. Synphasec,\ntrigoa. Trigoa,\ntrinovum. TriNovum,\ntriquilar. Triquilar,\ntrisiston. Trisiston,\nvalette. Valette,\nvatrice. Vatrice,\nvelafee. Velafee,\nverana. Verana,\nyasmin. Yasmin,\nyasminelle. Yasminelle,\nyaz. Yaz,\nzoely. Zoely",
      "maxValue": "zoely",
      "minValue": "28_mini",
      "@type": "propertyValue"
    },
    {
      "name": "other_pill_name",
      "description": "Sie haben angegeben, dass Ihre Pille in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihrer Pille.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_hormonal_other",
      "description": "Welches hormonelle Verhütungsmittel verwenden Sie?",
      "value": "nuvaring. NuvaRing,\ncirclet. Circlet,\nevra. Evra,\nmirena. Mirena,\ndepo_provera. Depo Provera,\ndepo_clinovir. Depo Clinovir,\nimplanon. Implanon NXT,\nother. Der Name meines Verhütungsmittels kommt in dieser Liste nicht vor.",
      "maxValue": "other",
      "minValue": "circlet",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_hormonal_other_name",
      "description": "Sie haben angegeben, dass Ihr Verhütungsmittel in der Liste nicht vorkommt. Bitte nennen Sie hier den Namen Ihres Verhütungsmittels.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_pill_estrogen",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (*µ*g) Östrogen Ihre Pille enthält. Die meisten Pillen enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (*µ*g)  zu erhalten.",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_pill_gestagen_type",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, welcher Typ Gestagen verwendet wird.",
      "value": "CMA. Chlormadinonacetat,\nCPA. Cyproteronacetat,\nDNG. Dienogest,\nDSG. Desogestrel,\nDSP. Drospirenon,\nGSD. Gestoden,\nLYN. Lynestrenol,\nLNG. Levonorgestrel,\nNEA. Norethisteronacetat,\nNES. Norethisteron,\nNGT. Norgestimat,\nother_gestagen. Kommt in dieser Liste nicht vor.",
      "maxValue": "other_gestagen",
      "minValue": "CMA",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_pill_gestagen",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihrer Pille nach, wieviel Mikrogramm (*µ*g) des jeweiligen Gestagens Ihre Pille enthält. Die meisten Pillen enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (*µ*g)  zu erhalten.\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_estrogen",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (*µ*g) Östrogen Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 0 und 50 Mikrogramm Östrogen. Manchmal wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (*µ*g)  zu erhalten.                                                                                                                                                    ",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_gestagen_type",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, welcher Typ Gestagen verwendet wird.",
      "value": "CMA. Chlormadinonacetat,\nCPA. Cyproteronacetat,\nDNG. Dienogest,\nDSG. Desogestrel,\nDSP. Drospirenon,\nGSD. Gestoden,\nLYN. Lynestrenol,\nLNG. Levonorgestrel,\nNEA. Norethisteronacetat,\nNES. Norethisteron,\nNGT. Norgestimat,\nother_gestagen. Kommt in dieser Liste nicht vor.",
      "maxValue": "other_gestagen",
      "minValue": "CMA",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_gestagen",
      "description": "Bitte lesen Sie in der Packungsbeilage Ihres Verhütungsmittels nach, wieviel Mikrogramm (*µ*g) des jeweiligen Gestagens Ihr Verhütungsmittel enthält. Die meisten Verhütungsmittel enthalten zwischen 50 und 3000 Mikrogramm Gestagen. Häufig wird die Gewichtsangabe auch in Milligramm (mg) gemacht. Diese Zahl müssen Sie dann mit 1000 multiplizieren, um Mikrogramm (*µ*g)  zu erhalten.",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_app",
      "description": "Benutzen Sie eine Zyklus-App? ",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_app_name",
      "description": "Wie heißt diese App?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hormonal_contraception_last3m",
      "description": "Haben Sie in den letzten drei Monaten hormonell verhütet?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_meeting_partner",
      "description": "Haben Sie hormonell verhütet (z.B. Pille), als Sie Ihren Partner kennengelernt haben?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "self_rated_health",
      "description": "Bitte beurteilen Sie Ihren allgemeinen Gesundheitszustand zum jetzigen Zeitpunkt.",
      "value": "1. sehr gut,\n2. gut,\n3. teils gut/teils schlecht,\n4. schlecht,\n5. sehr schlecht,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "height",
      "description": "Bitte geben Sie Ihre Körpergröße in cm an (ohne Schuhe).",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "weight",
      "description": "Bitte geben Sie Ihr Gewicht in kg an (ohne Kleidung).",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hormonal_med",
      "description": "Haben Sie in den letzten 3 Monaten hormonelle Medikamente (außer Verhütung) genommen?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hormonal_med_name",
      "description": "Welche?",
      "value": "1. Insulin,\n2. Thyroxin,\n3. Escitalopram,\n4. Mönchspfeffer",
      "maxValue": "4",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "psychoactive_med",
      "description": "Nehmen Sie psychoaktive Medikamente (z. B. gegen Depression)?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "psychoactive_med_name",
      "description": "Welche?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alcohol_weekly",
      "description": "Wie viel Gläser Alkohol trinken Sie im Schnitt in der Woche?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "cigarettes_daily",
      "description": "Wie viele Zigaretten rauchen Sie im Schnitt am Tag?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sport_weekly",
      "description": "Wie viele Stunden pro Woche treiben Sie schweißtreibenden Sport?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sport_kinds",
      "description": "Wenn Sie Sport treiben – welche Sportarten sind dies typischerweise?\n<small><em>Wählen Sie aus der Liste der vorgeschlagenen Sportarten aus und/oder fügen Sie „Ihre“ Sportart(en) hinzu. Sie können mehrere Sportarten angeben oder auch gar keine.<\/em><\/small>",
      "value": "1. Laufen,\n2. Schwimmen,\n3. Fitness-/Krafttraining (Geräte),\n4. Aerobic (z.B. Step Aerobic; Zumba),\n5. Klettern/Bouldern,\n6. Yoga,\n7. Mannschaftssport (z.B. Hand-;Volley-; Fussball)",
      "maxValue": "7",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "meat_eating",
      "description": "Essen Sie Fleisch und tierische Produkte?",
      "value": "1_every_day. ja, sehr viel,\n2_frequently. ja, oft,\n3_rarely. ja, selten,\n4_only_poultry. nur Geflügel,\n5_only_fish. nur Fisch,\n6_vegetarian. nein, Vegetarierin,\n7_vegan. nein, Veganerin",
      "maxValue": "7_vegan",
      "minValue": "1_every_day",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menarche",
      "description": "Wie alt waren Sie, als Sie Ihre erste Monatsblutung (Periode, Tage, Menstruation) hatten?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menarche_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±0.5 Jahre,\n3. ±1 Jahr,\n4. ±2 Jahre,\n5. ±3 Jahre,\n6. ±4 Jahre,\n7. unsicherer,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "number_sexual_partner",
      "description": "Mit wie vielen Personen haben Sie insgesamt in Ihrem Leben Geschlechtsverkehr gehabt?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "number_sexual_partner_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1,\n3. ±2,\n4. ±3,\n5. ±5,\n6. ±10,\n7. ±20,\n8. unsicherer,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "first_time",
      "description": "Wie alt waren Sie, als Sie das erste Mal Geschlechtsverkehr hatten?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "first_time_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±0.5 Jahre,\n3. ±1 Jahr,\n4. ±2 Jahre,\n5. ±3 Jahre,\n6. ±4 Jahre,\n7. unsicherer,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mother_menopause_yes",
      "description": "Hat Ihre Mutter die Menopause erreicht?",
      "value": "1. Ja,\n2. Nein, ist zur Zeit in den Wechseljahren,\n3. Nein, noch nicht,\n4. Nein, vorher verstorben,\nNA. Item was never rendered for this user.",
      "maxValue": 4,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mother_menopause_age",
      "description": "Wie alt war Ihre Mutter beim Einsetzen ihrer Menopause?\n\n*Wenn Sie es den Zeitpunkt nicht genau benennen können, versuchen Sie sich zu erinnern, wann Ihre Mutter über typische Begleiterscheinungen (z.B. Hitzewallungen, etc.) gesprochen hat. Idealerweise fragen Sie Ihre Mutter kurz (telefonisch), aber Sie können auch fortfahren, ohne dies zu tun, wenn es grade nicht geht.*",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mother_menopause_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau <small>(ich habe sie gefragt)<\/small>,\n2. ±0.5 Jahre,\n3. ±1 Jahr,\n4. ±2 Jahre,\n5. ±3 Jahre,\n6. ±4 Jahre,\n7. unsicherer <small>(ich habe geraten)<\/small>,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menopause_yes",
      "description": "Ist bei Ihnen selbst die Menopause eingetreten?",
      "value": "1. Ja,\n2. Nein, bin zur Zeit in den Wechseljahren,\n3. Nein, noch nicht,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 3,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menopause_age",
      "description": "Wie alt waren Sie selbst zum Eintritt Ihrer Menopause?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menopause_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±0.5 Jahre,\n3. ±1 Jahr,\n4. ±2 Jahre,\n5. ±3 Jahre,\n6. ±4 Jahre,\n7. ±7 Jahre,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_regular",
      "description": "Haben Sie zur Zeit regelmäßig (ungefähr monatlich) Ihre Periode?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_last",
      "description": "Nennen Sie bitte den ersten Tag (Start) Ihrer letzten Periode (Menstruationsblutung). Wenn möglich schauen Sie das Datum bitte in Ihrem Kalender nach.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_last_certainty",
      "description": "Wie sicher sind Sie bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1 Tag,\n3. ±2 Tage,\n4. ±3 Tage,\n5. ±4 Tage,\n6. ±5 Tage,\n7. ±6 Tage,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_length",
      "description": "Wie lange dauert Ihr Menstruationszyklus (Tage vom Beginn einer Monatsblutung bis zum Beginn der nächsten Monatsblutung; meist zwischen 25-35 Tagen)?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_length_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1 Tag,\n3. ±2 Tage,\n4. ±3 Tage,\n5. ±4 Tage,\n6. ±5 Tage,\n7. ±6 Tage,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_regularity",
      "description": "Wie regelmäßig war in den letzten 3 Monaten Ihr Menstruationszyklus?",
      "value": "1. Völlig (gar keine Schwankungen),\n2. Sehr (max. 1-2 Tage Schwankungen),\n3. Etwas (3-5 Tage Schwankungen),\n4. Kaum (über 5 Tage Schwankungen),\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 4,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_regularity_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1 Tag,\n3. ±2 Tage,\n4. ±3 Tage,\n5. ±4 Tage,\n6. ±5 Tage,\n7. ±6 Tage,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "free_not_covered",
      "description": "Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an.\n<small>optional<\/small>",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hetero_relationship",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    },
    {
      "name": "ended_date",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_pill_estrogen",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_pill_gestagen",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_other_pill_gestagen_type",
      "@type": "propertyValue"
    },
    {
      "name": "hormonal_contraception",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_method_broad",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_hormonal_pill_estrogen",
      "@type": "propertyValue"
    },
    {
      "name": "contraception_hormonal_pill_gestagen_type",
      "@type": "propertyValue"
    },
    {
      "name": "estrogen_progestogen",
      "@type": "propertyValue"
    },
    {
      "name": "living_situation",
      "@type": "propertyValue"
    }
  ]
}`

Personality

Metadata

Description

Dataset name: s2_initial

The dataset has N=1512 rows and 191 columns. 0 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
created
modified
ended
expired
bfi_open_1
narq_5
narq_3
bfi_agree_2
pvd_infectability_1
bfi_consc_2r
soi_r_attitude_6r
asendorpf_shyness_4r
bfi_neuro_2r
bfi_open_2
bfi_extra_1
bfi_extra_3
bfi_agree_3r
soi_r_attitude_4
narq_15
bfi_consc_3
soi_r_attitude_5
narq_2
asendorpf_shyness_2
bfi_agree_1r
bfi_consc_1
narq_11
bfi_neuro_1
bfi_extra_2r
bfi_neuro_3
narq_18
bfi_open_3
asendorpf_shyness_5
bfi_extra_4
narq_16
bfi_agree_4
bfi_consc_9r
bfi_neuro_4
bfi_open_4
bfi_extra_5r
bfi_agree_5
narq_1
bfi_consc_4r
bfi_neuro_5r
bfi_open_5
bfi_extra_6
narq_14
bfi_agree_6r
bfi_consc_5
asendorpf_shyness_3r
pvd_germ_aversion_2
pvd_germ_aversion_3R
bfi_neuro_8
pvd_infectability_3R
pvd_germ_aversion_1
feel_safe_walking_dark
feel_safe_violent_crime
feel_safe_sexual_assault
feel_safe_theft
bfi_open_6
narq_17
bfi_extra_7r
bfi_agree_7
narq_4
asendorpf_shyness_1
bfi_consc_6
bfi_neuro_6r
bfi_open_7r
narq_13
bfi_extra_8
bfi_agree_8r
narq_6
bfi_consc_7
bfi_neuro_7
narq_7
bfi_open_8
narq_12
bfi_open_9r
bfi_agree_9
narq_8
bfi_consc_8r
narq_9
narq_10
bfi_open_10
pvd_infectability_2
pvd_germ_aversion_4R
spms_partner_1
spms_partner_2
spms_partner_3R
satisfaction_sexual_intercourse
satisfaction_single_life
investment_potential_partner
timeperiod_potential_partner
characteristics_potential_partner
quantity_potential_partner
sexual_partner
fling_frequency
fling_frequency_2
relationship_importance
relationship_importance_partner
partner_attractiveness_longterm
partner_attractiveness_shortterm
partner_attractiveness_face
partner_attractiveness_body
attractiveness_warmth
partner_attractiveness_trust
net_income_partner
partner_sexiness
partner_strength
partner_feel_safe
spms_self_1
spms_self_2
spms_self_3R
meet_potential_partner
partner_height
meet_potential_partner_other
partner_weight
soi_r_behavior_1
soi_r_behavior_2
soi_r_behavior_3
soi_r_desire_9
soi_r_desire_7
soi_r_desire_8
relationship_problems
relationship_satisfaction_overall
relationship_conflict
relationship_satisfaction_2
relationship_satisfaction_3
alternatives_1
alternatives_2
alternatives_3
alternatives_4
alternatives_5
alternatives_6
investment_1
investment_2
investment_3
commitment_1
commitment_2
commitment_3
communal_strength_1
communal_strength_2R
communal_strength_3
communal_strength_4
sexual_communal_strength_1
sexual_communal_strength_2
sexual_communal_strength_3
ecr_avo_1R
ecr_anx_1
ecr_avo_2
ecr_anx_2
ecr_anx_3
ecr_avo_3R
ecr_avo_4
ecr_anx_4R
ecr_avo_5R
ecr_anx_5
ecr_avo_6
ecr_anx_6
free_not_covered
narq
bfi_open
bfi_extra
bfi_agree
soi_r_attitude
bfi_consc
asendorpf_shyness
bfi_neuro
pvd_germ_aversion
pvd_infectability
spms_partner
spms_self
relationship_satisfaction
alternatives
investment
commitment
communal_strength
sexual_communal_strength
ecr_avo
ecr_anx
short
soi_r_desire
soi_r_behavior_1_discrete
soi_r_behavior_2_discrete
soi_r_behavior_3_discrete
soi_r_behavior
soi_r
spms_rel
partner_attractiveness_sexual
relationship_conflict_R
relationship_problems_R

Survey overview

1411 completed rows, 1484 who entered any information, 28 only viewed the first page. There are 13 expired rows (people who did not finish filling out in the requested time frame). In total, there are 1512 rows including unfinished and expired rows.

There were 1512 unique participants, of which 1411 finished filling out at least one survey.

This survey was not repeated.

The first session started on 2016-05-02 21:46:49, the last session on 2017-01-14 22:45:37.

Starting date times

People took on average 1217.46 minutes (median 14.4) to answer the survey.

Duration people took for answering the survey

#Variables

feel_safe_walking_dark

Ich fühle mich in meiner Gegend sicher, wenn ich alleine in der Dunkelheit unterwegs bin.

Distribution

Distribution of values for feel_safe_walking_dark

93 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	feel_safe_walking_dark	Ich fühle mich in meiner Gegend sicher, wenn ich alleine in der Dunkelheit unterwegs bin.	0			55

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

feel_safe_violent_crime

Ich fühle mich in meiner Gegend sicher vor Gewaltverbrechen.

Distribution

Distribution of values for feel_safe_violent_crime

93 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	feel_safe_violent_crime	Ich fühle mich in meiner Gegend sicher vor Gewaltverbrechen.	0			55

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

feel_safe_sexual_assault

Ich fühle mich in meiner Gegend sicher vor sexuellen Übergriffen.

Distribution

Distribution of values for feel_safe_sexual_assault

93 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	feel_safe_sexual_assault	Ich fühle mich in meiner Gegend sicher vor sexuellen Übergriffen.	0			55

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

feel_safe_theft

Ich fühle mich in meiner Gegend sicher vor Diebstahl.

Distribution

Distribution of values for feel_safe_theft

93 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	feel_safe_theft	Ich fühle mich in meiner Gegend sicher vor Diebstahl.	0			55

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

satisfaction_sexual_intercourse

Der Sex mit meinem Partner ist sehr befriedigend.

Distribution

Distribution of values for satisfaction_sexual_intercourse

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for satisfaction_sexual_intercourse

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	satisfaction_sexual_intercourse	Der Sex mit meinem Partner ist sehr befriedigend.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

satisfaction_single_life

Ich bin zufrieden mit meinem Singleleben.

Distribution

Distribution of values for satisfaction_single_life

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for satisfaction_single_life

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	satisfaction_single_life	Ich bin zufrieden mit meinem Singleleben.	0	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

investment_potential_partner

Ich investiere viel, um jemanden kennenzulernen.

Distribution

Distribution of values for investment_potential_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for investment_potential_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	investment_potential_partner	Ich investiere viel, um jemanden kennenzulernen.	0	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

timeperiod_potential_partner

Folgende Art von Partnerschaft, suche ich derzeit eher.

Distribution

Distribution of values for timeperiod_potential_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		timeperiod_potential_partner	Folgende Art von Partnerschaft, suche ich derzeit eher.	0	mc_vertical	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1	no_interest
2	one_night
3	short
4	long

characteristics_potential_partner

Ein Partner, der für mich in Frage käme, sollte folgende Eigenschaften haben.

Distribution

Distribution of values for characteristics_potential_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		characteristics_potential_partner	Ein Partner, der für mich in Frage käme, sollte folgende Eigenschaften haben.	0	square square100	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1	body
2	face
3	money
4	social_status
5	intelligence
6	humor
7	creativity
8	trustworthiness
9	personality

quantity_potential_partner

Es befinden sich viele annehmbare Singles in meiner Umgebung.

Distribution

Distribution of values for quantity_potential_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for quantity_potential_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	quantity_potential_partner	Es befinden sich viele annehmbare Singles in meiner Umgebung.	0	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

sexual_partner

Wenn ich sexuell aktiv werde, dann üblicherweise mit Männern…

Distribution

Distribution of values for sexual_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		sexual_partner	Wenn ich sexuell aktiv werde, dann üblicherweise mit Männern…	0	mc_vertical	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
1	longterm
2	friends
3	met_before
4	new

fling_frequency

Im Monat habe ich durchschnittlich etwa so oft sexuellen Kontakt zu einer anderen Person.

Distribution

Distribution of values for fling_frequency

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for fling_frequency

Item

Item options
type	name	label	optional	showif	value	item_order
number	fling_frequency	Im Monat habe ich durchschnittlich etwa so oft sexuellen Kontakt zu einer anderen Person.	0	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

fling_frequency_2

Im Monat habe ich durchschnittlich etwa so oft die Möglichkeit zu sexuellen Kontakt zu einer anderen Person.

Distribution

Distribution of values for fling_frequency_2

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for fling_frequency_2

Item

Item options
type	name	label	optional	showif	value	item_order
number	fling_frequency_2	Im Monat habe ich durchschnittlich etwa so oft die Möglichkeit zu sexuellen Kontakt zu einer anderen Person.	0	s1_demo$hetero_relationship == 0		82

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

relationship_importance

Mir ist die Beziehung zu meinem Partner sehr wichtig.

Distribution

Distribution of values for relationship_importance

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for relationship_importance

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	relationship_importance	Mir ist die Beziehung zu meinem Partner sehr wichtig.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

relationship_importance_partner

Meinem Partner ist die Beziehung zu mir sehr wichtig.

Distribution

Distribution of values for relationship_importance_partner

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for relationship_importance_partner

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	relationship_importance_partner	Meinem Partner ist die Beziehung zu mir sehr wichtig.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_attractiveness_longterm

Mein Partner ist sehr attraktiv für eine langfristige Beziehung (z.B. als möglicher Ehepartner).

Distribution

Distribution of values for partner_attractiveness_longterm

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_attractiveness_longterm

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	attractiveness_ltp	Mein Partner ist sehr attraktiv für eine langfristige Beziehung (z.B. als möglicher Ehepartner).	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

attractiveness_warmth

Ich fühle mich bei meinem Partner sehr geborgen.

Distribution

Distribution of values for attractiveness_warmth

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for attractiveness_warmth

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	attractiveness_warmth	Ich fühle mich bei meinem Partner sehr geborgen.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_attractiveness_trust

Das Vertrauen zwischen meinem Partner und mir ist sehr stark.

Distribution

Distribution of values for partner_attractiveness_trust

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_attractiveness_trust

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	attractiveness_trustworthiness	Das Vertrauen zwischen meinem Partner und mir ist sehr stark.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

net_income_partner

Wie viel Geld hat Ihr Partner monatlich zur Verfügung (netto)?

Distribution

Distribution of values for net_income_partner

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		net_income_partner	Wie viel Geld hat Ihr Partner monatlich zur Verfügung (netto)?	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1	euro_lt_500
2	euro_500_1000
3	euro_1000_2000
4	euro_2000_3000
5	euro_gt_3000
6	dont_know
7	dont_tell

partner_strength

Mein Partner ist körperlich stärker als viele andere Männer.

Distribution

Distribution of values for partner_strength

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_strength

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	partner_strength	Mein Partner ist körperlich stärker als viele andere Männer.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

partner_feel_safe

Mit meinem Partner fühle ich mich sehr sicher.

Distribution

Distribution of values for partner_feel_safe

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_feel_safe

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	partner_feel_safe	Mit meinem Partner fühle ich mich sehr sicher.	0	s1_demo$hetero_relationship == 1		82

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

meet_potential_partner

Folgendes tue ich, um einen potentiellen Partner kennen zu lernen.

Distribution

Distribution of values for meet_potential_partner

1041 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		meet_potential_partner	Folgendes tue ich, um einen potentiellen Partner kennen zu lernen.	0	mc_vertical	s1_demo$hetero_relationship == 0		83

Value labels

Response choices
name	value
1	no_interest
2	dating_app
3	online_dating
4	contact_ad
5	going_out
6	sports
7	social_networks
8	friends
9	other

partner_height

Was ist die Körpergröße Ihres Partners in cm (ohne Schuhe)?

Distribution

Distribution of values for partner_height

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_height

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	80,230	partner_height	Was ist die Körpergröße Ihres Partners in cm (ohne Schuhe)?	0	s1_demo$hetero_relationship == 1		83

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

meet_potential_partner_other

Andere:

Distribution

Distribution of values for meet_potential_partner_other

1505 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
meet_potential_partner_other	Andere:	text	character	0	meet_potential_partner == ‘other’		84	1505	0.0046	7	0	3	85	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	meet_potential_partner_other	Andere:	0	meet_potential_partner == ‘other’		84

Value labels

Response choices
name	value

partner_weight

Was ist das Gewicht Ihres Partners in kg (ohne Kleidung)?

Distribution

Distribution of values for partner_weight

570 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for partner_weight

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	40,200	partner_weight	Was ist das Gewicht Ihres Partners in kg (ohne Kleidung)?	0	s1_demo$hetero_relationship == 1		84

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

soi_r_behavior_1

Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?

Distribution

Distribution of values for soi_r_behavior_1

101 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
number	soi_r_behavior_1	Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?	0			117

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

soi_r_behavior_2

Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?

Distribution

Distribution of values for soi_r_behavior_2

101 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
number	soi_r_behavior_2	Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?	0			117

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

soi_r_behavior_3

Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?

Distribution

Distribution of values for soi_r_behavior_3

101 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
number	soi_r_behavior_3	Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?	0			117

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

relationship_problems

Es gibt viele Probleme in meiner Beziehung.

Distribution

Distribution of values for relationship_problems

572 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for relationship_problems

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	relationship_problems	Es gibt viele Probleme in meiner Beziehung.	0	s1_demo$hetero_relationship == 1		119

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

relationship_conflict

Es gibt oft Streit/Meinungsverschiedenheiten in meiner Partnerschaft.

Distribution

Distribution of values for relationship_conflict

572 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for relationship_conflict

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	relationship_conflict	Es gibt oft Streit/Meinungsverschiedenheiten in meiner Partnerschaft.	0	s1_demo$hetero_relationship == 1		119

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

free_not_covered

Distribution

Distribution of values for free_not_covered

1419 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
free_not_covered	Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an. <small>optional</small>	textarea	character	1			160	1419	0.0615	93	0	1	698	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	free_not_covered	Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an. <small>optional</small>	1			160

Value labels

Response choices
name	value

Scale: narq

Overview

Reliability: ω_ordinal [95% CI] = 0.86 [0.85;0.87].

Missing: 93.

Likert plot of scale narq items

Distribution of scale narq

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	narq_5, narq_3, narq_15, narq_2, narq_11, narq_18, narq_16, narq_1, narq_14, narq_17, narq_4, narq_13, narq_6, narq_7, narq_12, narq_8, narq_9 & narq_10
Observations:	1419
Positive correlations:	145
Number of correlations:	153
Percentage positive correlations:	95

Estimates assuming interval level


Omega (total):	0.84
Omega (hierarchical):	0.51
Revelle’s Omega (total):	0.88
Greatest Lower Bound (GLB):	0.90
Coefficient H:	0.85
Coefficient Alpha:	0.84

Confidence intervals


Omega (total):	[0.83; 0.85]
Coefficient Alpha	[0.82; 0.85]

Estimates assuming ordinal level


Ordinal Omega (total):	0.86
Ordinal Omega (hierarch.):	0.82
Ordinal Coefficient Alpha:	0.87

Confidence intervals


Ordinal Omega (total):	[0.85; 0.87]
Ordinal Coefficient Alpha	[0.86; 0.88]

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.877, 2.757, 1.394, 1.095, 0.974, 0.801, 0.736, 0.701, 0.669, 0.609, 0.578, 0.503, 0.465, 0.463, 0.394, 0.352, 0.329 & 0.305

Factor analysis (reproducing only shared variance)

	ML1	ML4	ML3	ML2
narq_5	0.248	0.366	-0.081	0.020
narq_3	0.107	0.565	-0.095	0.117
narq_15	-0.027	0.691	0.021	0.008
narq_2	0.027	0.388	0.118	0.129
narq_11	0.420	-0.053	-0.025	-0.034
narq_18	-0.092	0.076	-0.028	0.514
narq_16	0.047	0.189	-0.019	0.662
narq_1	-0.061	0.692	-0.031	-0.027
narq_14	0.060	-0.083	0.459	0.029
narq_17	-0.007	0.046	0.855	0.002
narq_4	0.548	0.073	0.021	0.063
narq_13	0.030	-0.028	0.781	0.004
narq_6	0.797	-0.033	-0.015	-0.029
narq_7	-0.008	-0.072	0.029	0.855
narq_12	0.535	0.007	-0.042	0.178
narq_8	0.037	0.641	0.131	0.023
narq_9	0.765	-0.015	0.028	-0.032
narq_10	0.631	0.063	0.100	-0.028

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3	TC4
narq_5	0.240	0.599	-0.133	-0.115
narq_3	0.142	0.577	-0.127	0.219
narq_15	-0.033	0.698	0.021	0.118
narq_2	0.010	0.404	0.185	0.230
narq_11	0.627	-0.135	-0.101	-0.034
narq_18	-0.092	0.037	-0.010	0.706
narq_16	0.082	0.232	0.015	0.699
narq_1	-0.121	0.788	-0.032	0.010
narq_14	-0.035	-0.150	0.731	0.076
narq_17	0.049	0.061	0.825	0.013
narq_4	0.729	-0.025	0.002	0.143
narq_13	0.038	0.001	0.830	-0.011
narq_6	0.691	0.116	0.127	-0.181
narq_7	0.031	0.028	0.062	0.817
narq_12	0.737	-0.121	-0.067	0.299
narq_8	0.021	0.645	0.173	0.123
narq_9	0.663	0.122	0.172	-0.167
narq_10	0.613	0.146	0.205	-0.115

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
narq_5	3.69767441860465	4	0.971299242299997	0.985545149802888	1	0.0261628666254947	1	3	5	5	-0.441620454841714	-0.391039013913282	0.132840028188865	1419	1419
narq_3	2.72797744890768	3	1.08533095576754	1.04179218453948	1	0.0276560338012321	1	2	4	5	0.0590173018996267	-0.712225429009423	0.148343904157858	1419	1419
narq_15	2.74489076814658	3	1.23670695209384	1.11207326741265	2	0.0295217571502576	1	2	4	5	0.102532850953908	-0.787897328649723	0.140239605355884	1419	1419
narq_2	1.6814658210007	1	0.799733816003045	0.894278377242258	1	0.0237400446996593	1	NA	2	5	1.26743696571477	1.07344688038982	0.140944326990839	1419	1419
narq_11	2.95137420718816	3	1.07168181967277	1.03522066230962	2	0.0274815822708678	1	2	4	5	0.0629204773948583	-0.714527563706265	0.148343904157858	1419	1419
narq_18	3.14023960535588	3	0.889345781758942	0.943051314488741	1	0.025034800046351	1	2	4	5	-0.181440966587617	-0.222975211538846	0.146582100070472	1419	1419
narq_16	2.67441860465116	3	1.16472594876505	1.07922469799623	1	0.0286497395256445	1	2	4	5	0.141661818809007	-0.734389822854693	0.150105708245243	1419	1419
narq_1	2.97885835095137	3	1.12790250389883	1.0620275438513	2	0.0281932136624492	1	2	4	5	-0.0710697895635157	-0.453617785647023	0.11169837914024	1419	1419
narq_14	1.10852713178295	1	0.172980833360667	0.415909645669185	0	0.0110409843628939	1	NA	2	5	4.59713221965587	24.6656865134064	0.0260747004933051	1419	1419
narq_17	1.46723044397463	1	0.628509319918773	0.79278579699612	1	0.0210457624123505	1	NA	2	5	1.81281265549157	3.08135634069116	0.101127554615927	1419	1419
narq_4	2.02748414376321	2	1.08316510464967	1.04075218214985	2	0.0276284252803892	1	1	3	5	0.824629655574526	-0.127441250308918	0.171952078928823	1419	1419
narq_13	1.67512332628612	1	0.871108500294711	0.933331934680642	1	0.0247767836199573	1	NA	2	5	1.31816874619511	1.05068045797274	0.12015503875969	1419	1419
narq_6	2.54122621564482	2	1.57992825556049	1.25695197026795	3	0.0333677932049591	1	1	4	5	0.376042962170525	-0.962607258961765	0.126849894291755	1419	1419
narq_7	3.00070472163495	3	1.04301783870124	1.02128244805306	2	0.0271115701606515	1	2	4	5	-0.0769894738538039	-0.457500125874986	0.124383368569415	1419	1419
narq_12	1.75968992248062	2	0.830080580794	0.91108758129721	1	0.0241862718094557	1	1	3	5	1.1703057167437	0.890261941928853	0.167371388301621	1419	1419
narq_8	2.24242424242424	2	1.17532162243023	1.08412251264801	2	0.0287797598210278	1	1	3	5	0.465402337969955	-0.615637460736991	0.140591966173362	1419	1419
narq_9	2.05426356589147	2	1.27138343118925	1.12755639822993	2	0.0299327815326501	1	1	3	5	0.845004882000305	-0.225588617252515	0.140239605355884	1419	1419
narq_10	2.07117688513037	2	1.25938725994487	1.12222424672829	2	0.029791231073402	1	1	3	5	0.777093465856214	-0.434429447887318	0.145172656800564	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
narq_5	Ich genieße meine Erfolge sehr.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.687	0.9881	6	▁▂▁▆▁▇▁▅
narq_3	Ich zeige anderen, was für ein besonderer Mensch ich bin.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.728	1.0411	6	▃▇▁▇▁▅▁▁
narq_15	Ich ziehe viel Kraft daraus, eine ganz besondere Person zu sein.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.742	1.1093	6	▃▇▁▇▁▆▁▂
narq_2	Ich werde einmal berühmt sein.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	1	5	1.681	0.8954	6	▇▅▁▂▁▁▁▁
narq_11	Ich reagiere häufig gereizt auf Kritik.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.949	1.0344	6	▂▇▁▇▁▆▁▂
narq_18	Ich verhalte mich im Umgang mit anderen meist überaus gewandt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	3.143	0.9427	6	▁▃▁▇▁▆▁▁
narq_16	Mit meinen besonderen Beiträgen schaffe ich es im Mittelpunkt zu stehen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.678	1.0777	6	▃▇▁▇▁▅▁▁
narq_1	Ich bin großartig.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.978	1.0576	6	▂▃▁▇▁▅▁▂
narq_14	Andere Menschen sind nichts wert.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	1	5	1.109	0.4168	6	▇▁▁▁▁▁▁▁
narq_17	Die meisten Menschen sind ziemliche Versager.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	1	5	1.467	0.7928	6	▇▂▁▁▁▁▁▁
narq_4	Ich reagiere genervt, wenn eine andere Person mir die Schau stiehlt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.027	1.0408	6	▇▇▁▃▁▂▁▁
narq_13	Die meisten Menschen werden es zu nichts bringen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	1	5	1.675	0.9333	6	▇▃▁▂▁▁▁▁
narq_6	Es freut mich insgeheim, wenn meine Gegner scheitern.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.541	1.2570	6	▇▇▁▆▁▅▁▂
narq_7	In Gesprächen gelingt es mir meist, die Aufmerksamkeit der Anwesenden auf mich zu ziehen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	3.001	1.0213	6	▂▅▁▇▁▅▁▂
narq_12	Ich ertrage es nur schlecht, wenn eine andere Person Mittelpunkt des Geschehens ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	1.760	0.9111	6	▇▆▁▂▁▁▁▁
narq_8	Ich habe es verdient, als große Persönlichkeit angesehen zu werden.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.242	1.0841	6	▇▇▁▇▁▂▁▁
narq_9	Ich will, dass meine Konkurrenten scheitern.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.054	1.1276	6	▇▆▁▃▁▂▁▁
narq_10	Ich genieße es, wenn ein anderer Mensch mir unterlegen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.071	1.1222	6	▇▆▁▃▁▂▁▁

Scale: bfi_open

Overview

Reliability: ω_ordinal [95% CI] = 0.85 [0.84;0.86].

Missing: 93.

Likert plot of scale bfi_open items

Distribution of scale bfi_open

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	bfi_open_1, bfi_open_2, bfi_open_3, bfi_open_4, bfi_open_5, bfi_open_6, bfi_open_7r, bfi_open_8, bfi_open_9r & bfi_open_10
Observations:	1419
Positive correlations:	45
Number of correlations:	45
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.82
Omega (hierarchical):	0.68
Revelle’s Omega (total):	0.86
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.84
Coefficient Alpha:	0.82

Confidence intervals


Omega (total):	[0.8; 0.83]
Coefficient Alpha	[0.8; 0.83]

Estimates assuming ordinal level


Ordinal Omega (total):	0.85
Ordinal Omega (hierarch.):	0.85
Ordinal Coefficient Alpha:	0.85

Confidence intervals


Ordinal Omega (total):	[0.84; 0.86]
Ordinal Coefficient Alpha	[0.84; 0.86]

Eigen values

3.872, 1.352, 0.973, 0.883, 0.692, 0.567, 0.56, 0.497, 0.311 & 0.293

Factor analysis (reproducing only shared variance)

	ML1	ML2
bfi_open_1	0.820	-0.055
bfi_open_2	0.253	0.275
bfi_open_3	0.215	0.234
bfi_open_4	0.553	0.149
bfi_open_5	0.863	-0.021
bfi_open_6	-0.001	0.802
bfi_open_7r	0.268	0.036
bfi_open_8	0.502	0.182
bfi_open_9r	-0.009	0.853
bfi_open_10	0.022	0.609

Component analysis (reproducing full covariance matrix)

	TC1	TC2
bfi_open_1	0.858	-0.081
bfi_open_2	0.347	0.315
bfi_open_3	0.288	0.302
bfi_open_4	0.655	0.117
bfi_open_5	0.858	-0.028
bfi_open_6	0.002	0.851
bfi_open_7r	0.454	-0.073
bfi_open_8	0.645	0.149
bfi_open_9r	0.024	0.854
bfi_open_10	-0.042	0.785

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
bfi_open_1	3.40803382663848	4	1.03578872664057	1.01773706164243	1	0.0270174522282406	1	3	5	5	-0.390767425608948	-0.345781846260282	0.15292459478506	1419	1419
bfi_open_2	4.24524312896406	4	0.688755564965097	0.829912986381763	1	0.0220313628227126	1	3	5	5	-1.0396439373525	0.872050032518053	0.195207892882311	1419	1419
bfi_open_3	4.29175475687104	5	0.728641417951616	0.853604954268434	1	0.0226603038672081	1	4	NA	5	-1.08727222413103	0.522611337685383	0.166666666666667	1419	1419
bfi_open_4	4.00211416490486	4	1.03031992771882	1.01504676134591	2	0.0269460339194452	1	3	5	5	-0.8915377187735	0.177320272044884	0.17723749119098	1419	1419
bfi_open_5	3.49189570119803	4	1.02161974651888	1.01075206975741	1	0.0268320244869499	1	3	5	5	-0.373864554773889	-0.337345707247325	0.155038759689922	1419	1419
bfi_open_6	3.97181113460183	4	1.13601723933997	1.06584109478851	2	0.0282944504495813	1	3	5	5	-0.916727479091988	0.134314901906509	0.169485553206483	1419	1419
bfi_open_7r	3.39464411557435	3	1.18406156225555	1.08814592875016	1	0.0288865678134171	1	2	4	5	-0.297649579752449	-0.617118281579566	0.145525017618041	1419	1419
bfi_open_8	3.95560253699789	4	0.914106459683263	0.956089148397399	2	0.025380910125332	1	3	5	5	-0.754910786061553	0.0768393133009771	0.162790697674419	1419	1419
bfi_open_9r	3.99929527836505	4	1.29830697833453	1.13943274410319	2	0.0302480580607144	1	3	5	5	-0.963895025126894	-0.0521401859214166	0.139887244538407	1419	1419
bfi_open_10	3.05778717406624	3	1.27733529740943	1.13019259306077	2	0.0300027635256333	1	2	4	5	-0.09895213483261	-0.770743981787494	0.137420718816068	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
bfi_open_1	Ich sehe mich selbst als jemanden, der originell ist, neue Ideen entwickelt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.406	1.0195	6	▁▃▁▆▁▇▁▃
bfi_open_2	Ich sehe mich selbst als jemanden, der vielseitig interessiert ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	4.246	0.8279	6	▁▁▁▂▁▇▁▇
bfi_open_3	Ich sehe mich selbst als jemanden, der tiefsinnig ist, gern über Sachen nachdenkt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	5	5	4.293	0.8522	6	▁▁▁▂▁▅▁▇
bfi_open_4	Ich sehe mich selbst als jemanden, der eine lebhafte Vorstellungskraft hat, fantasievoll ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.998	1.0148	6	▁▂▁▃▁▇▁▇
bfi_open_5	Ich sehe mich selbst als jemanden, der erfinderisch und einfallsreich ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.491	1.0089	6	▁▃▁▇▁▇▁▃
bfi_open_6	Ich sehe mich selbst als jemanden, der künstlerische und ästhetische Eindrücke schätzt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.972	1.0658	6	▁▂▁▃▁▇▁▇
bfi_open_7r	Ich sehe mich selbst als jemanden, der routinemäßige und einfache Aufgaben bevorzugt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	3.395	1.0881	6	▁▃▁▇▁▇▁▃
bfi_open_8	Ich sehe mich selbst als jemanden, der gerne Überlegungen anstellt, mit Ideen spielt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.956	0.9561	6	▁▂▁▃▁▇▁▆
bfi_open_9r	Ich sehe mich selbst als jemanden, der nur wenig künstlerisches Interesse hat.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.999	1.1394	6	▁▂▁▂▁▅▁▇
bfi_open_10	Ich sehe mich selbst als jemanden, der sich gut in Musik, Kunst und Literatur auskennt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	3.058	1.1302	6	▂▆▁▇▁▇▁▂

Scale: bfi_extra

Overview

Reliability: ω_ordinal [95% CI] = 0.9 [0.89;0.9].

Missing: 93.

Likert plot of scale bfi_extra items

Distribution of scale bfi_extra

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	bfi_extra_1, bfi_extra_3, bfi_extra_2r, bfi_extra_4, bfi_extra_5r, bfi_extra_6, bfi_extra_7r & bfi_extra_8
Observations:	1419
Positive correlations:	28
Number of correlations:	28
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.88
Omega (hierarchical):	0.77
Revelle’s Omega (total):	0.90
Greatest Lower Bound (GLB):	0.89
Coefficient H:	0.90
Coefficient Alpha:	0.88

Confidence intervals


Omega (total):	[0.87; 0.89]
Coefficient Alpha	[0.87; 0.89]

Estimates assuming ordinal level


Ordinal Omega (total):	0.90
Ordinal Omega (hierarch.):	0.88
Ordinal Coefficient Alpha:	0.89

Confidence intervals


Ordinal Omega (total):	[0.89; 0.9]
Ordinal Coefficient Alpha	[0.89; 0.9]

Eigen values

4.327, 0.946, 0.662, 0.584, 0.492, 0.374, 0.328 & 0.286

Factor analysis (reproducing only shared variance)

	ML1
bfi_extra_1	0.761
bfi_extra_3	0.522
bfi_extra_2r	0.801
bfi_extra_4	0.584
bfi_extra_5r	0.800
bfi_extra_6	0.474
bfi_extra_7r	0.683
bfi_extra_8	0.823

Component analysis (reproducing full covariance matrix)

	PC1
bfi_extra_1	0.782
bfi_extra_3	0.616
bfi_extra_2r	0.819
bfi_extra_4	0.672
bfi_extra_5r	0.811
bfi_extra_6	0.573
bfi_extra_7r	0.727
bfi_extra_8	0.836

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
bfi_extra_1	3.79985905567301	4	1.06569814655228	1.03232656972117	2	0.0274047539709076	1	3	5	5	-0.617076468950068	-0.252024227290298	0.144115574348132	1419	1419
bfi_extra_3	3.43128964059197	3	0.875917306035061	0.935904538954193	1	0.0248450775002555	1	2	4	5	-0.231640977780597	-0.231078630486507	0.178646934460888	1419	1419
bfi_extra_2r	3.27554615926709	3	1.33516322406669	1.15549263263194	2	0.0306743933957135	1	2	4	5	-0.202204762350853	-0.871710491165895	0.125792811839323	1419	1419
bfi_extra_4	3.71176885130374	4	1.02758354032668	1.01369795320237	1	0.0269102276577333	1	3	5	5	-0.60411549538113	-0.138748326473191	0.116983791402396	1419	1419
bfi_extra_5r	3.77096546863989	4	1.27825372165583	1.13059883321001	2	0.0300135478178035	1	3	5	5	-0.644319889395021	-0.4435887366287	0.156448202959831	1419	1419
bfi_extra_6	3.36645525017618	3	1.06025618470267	1.02968742087231	1	0.0273346935588084	1	2	4	5	-0.288935950107599	-0.506672382878023	0.154686398872445	1419	1419
bfi_extra_7r	2.68428470754052	2	1.51097288362352	1.22921636973461	2	0.0326315074876816	1	1	4	5	0.298853281069789	-0.954943565660508	0.103241719520789	1419	1419
bfi_extra_8	3.50599013389711	4	1.19372290822417	1.09257627112443	1	0.0290041783122021	1	3	5	5	-0.419804728357477	-0.527383004631509	0.132840028188865	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
bfi_extra_1	Ich sehe mich selbst als jemanden, der gesprächig ist, sich gerne unterhält.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.803	1.0278	6	▁▂▁▅▁▇▁▆
bfi_extra_3	Ich sehe mich selbst als jemanden, der voller Energie und Tatendrang ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	3.427	0.9308	6	▁▂▁▇▁▇▁▂
bfi_extra_2r	Ich sehe mich selbst als jemanden, der eher zurückhaltend und reserviert ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	3.276	1.1523	6	▂▆▁▆▁▇▁▃
bfi_extra_4	Ich sehe mich selbst als jemanden, der begeisterungsfähig ist, andere mitreißen kann.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.706	1.0140	6	▁▂▁▅▁▇▁▅
bfi_extra_5r	Ich sehe mich selbst als jemanden, der eher still und wortkarg ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.769	1.1299	6	▁▃▁▅▁▇▁▇
bfi_extra_6	Ich sehe mich selbst als jemanden, der durchsetzungsfähig und energisch ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	3.360	1.0313	6	▁▃▁▇▁▇▁▃
bfi_extra_7r	Ich sehe mich selbst als jemanden, der manchmal schüchtern und gehemmt ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.684	1.2292	6	▅▇▁▅▁▅▁▂
bfi_extra_8	Ich sehe mich selbst als jemanden, der aus sich heraus geht, gesellig ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.506	1.0926	6	▁▃▁▆▁▇▁▅

Scale: bfi_agree

Overview

Reliability: ω_ordinal [95% CI] = 0.79 [0.77;0.81].

Missing: 93.

Likert plot of scale bfi_agree items

Distribution of scale bfi_agree

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	bfi_agree_2, bfi_agree_3r, bfi_agree_1r, bfi_agree_4, bfi_agree_5, bfi_agree_6r, bfi_agree_7, bfi_agree_8r & bfi_agree_9
Observations:	1419
Positive correlations:	36
Number of correlations:	36
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.78
Omega (hierarchical):	0.55
Revelle’s Omega (total):	0.81
Greatest Lower Bound (GLB):	0.83
Coefficient H:	0.81
Coefficient Alpha:	0.76

Confidence intervals


Omega (total):	[0.76; 0.79]
Coefficient Alpha	[0.75; 0.78]

Estimates assuming ordinal level


Ordinal Omega (total):	0.79
Ordinal Omega (hierarch.):	0.76
Ordinal Coefficient Alpha:	0.80

Confidence intervals


Ordinal Omega (total):	[0.77; 0.81]
Ordinal Coefficient Alpha	[0.78; 0.81]

Eigen values

3.149, 1.209, 0.934, 0.9, 0.75, 0.625, 0.595, 0.518 & 0.318

Factor analysis (reproducing only shared variance)

	ML1	ML2
bfi_agree_2	-0.044	0.687
bfi_agree_3r	0.373	0.052
bfi_agree_1r	0.424	0.131
bfi_agree_4	0.258	0.195
bfi_agree_5	0.172	0.343
bfi_agree_6r	0.715	0.024
bfi_agree_7	0.019	0.664
bfi_agree_8r	0.901	-0.028
bfi_agree_9	0.091	0.389

Component analysis (reproducing full covariance matrix)

	TC1	TC2
bfi_agree_2	-0.076	0.832
bfi_agree_3r	0.748	-0.203
bfi_agree_1r	0.726	-0.037
bfi_agree_4	0.512	0.112
bfi_agree_5	0.193	0.504
bfi_agree_6r	0.623	0.186
bfi_agree_7	0.057	0.741
bfi_agree_8r	0.738	0.141
bfi_agree_9	0.186	0.471

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
bfi_agree_2	3.89781536293164	4	0.708168707775097	0.841527603691702	1	0.022339691348957	1	3	5	5	-0.722456245541199	0.753900461993496	0.114517265680056	1419	1419
bfi_agree_3r	4.28188865398168	5	0.810468644857073	0.900260320605697	1	0.0238988449194262	1	4	NA	5	-1.24633183902132	1.10474997908307	0.158914728682171	1419	1419
bfi_agree_1r	3.09654686398872	3	1.16909243979799	1.08124578140124	2	0.0287033924055507	1	2	4	5	-0.0281772400927308	-0.754622250283923	0.139887244538407	1419	1419
bfi_agree_4	3.31219168428471	3	1.36297537648933	1.16746536414976	2	0.0309922286343185	1	2	4	5	-0.314353246381306	-0.773956612144722	0.126497533474278	1419	1419
bfi_agree_5	3.85412262156448	4	0.983641313585224	0.991786929529334	2	0.0263285646156085	1	3	5	5	-0.812354008453773	0.210948895813709	0.135658914728682	1419	1419
bfi_agree_6r	2.99788583509514	3	1.66783755818426	1.29144785345141	2	0.0342835413987765	1	2	4	5	-0.00786896143849787	-1.12113175259572	0.119097956307259	1419	1419
bfi_agree_7	4.24735729386892	4	0.626359372251064	0.791428690566032	1	0.0210097358593975	1	3	5	5	-0.965280837638447	0.838676078037697	0.210711768851304	1419	1419
bfi_agree_8r	3.27272727272727	3	1.63008077958713	1.27674616881631	2	0.0338932617506496	1	2	4	5	-0.22700354883649	-1.05660178260991	0.107117688513037	1419	1419
bfi_agree_9	4.10852713178295	4	0.923333442669553	0.960902410585775	1	0.0255086858408263	1	3	5	5	-1.00618440692128	0.517498277574388	0.178999295278365	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
bfi_agree_2	Ich sehe mich selbst als jemanden, der hilfsbereit und selbstlos gegenüber anderen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.897	0.8435	6	▁▁▁▃▁▇▁▃
bfi_agree_3r	Ich sehe mich selbst als jemanden, der häufig in Streitereien verwickelt ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	5	5	4.282	0.9002	6	▁▁▁▂▁▅▁▇
bfi_agree_1r	Ich sehe mich selbst als jemanden, der dazu neigt, andere zu kritisieren.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	3.096	1.0858	6	▂▆▁▇▁▇▁▂
bfi_agree_4	Ich sehe mich selbst als jemanden, der nicht nachtragend ist, anderen leicht vergibt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	3.311	1.1652	6	▂▅▁▆▁▇▁▃
bfi_agree_5	Ich sehe mich selbst als jemanden, der anderen Vertrauen schenkt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.857	0.9915	6	▁▂▁▃▁▇▁▅
bfi_agree_6r	Ich sehe mich selbst als jemanden, der sich kalt und distanziert verhalten kann.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	3.003	1.2897	6	▅▇▁▇▁▇▁▅
bfi_agree_7	Ich sehe mich selbst als jemanden, der rücksichtsvoll und einfühlsam zu anderen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	4.247	0.7914	6	▁▁▁▂▁▇▁▇
bfi_agree_8r	Ich sehe mich selbst als jemanden, der schroff und abweisend zu anderen sein kann.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	3.273	1.2767	6	▃▆▁▆▁▇▁▆
bfi_agree_9	Ich sehe mich selbst als jemanden, der sich kooperativ verhält, Zusammenarbeit dem Wettbewerb vorzieht.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	4.109	0.9609	6	▁▁▁▃▁▇▁▇

Scale: soi_r_attitude

Overview

Reliability: ω_ordinal [95% CI] = 0.89 [0.88;0.9].

Missing: 50.

Likert plot of scale soi_r_attitude items

Distribution of scale soi_r_attitude

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	soi_r_attitude_6r, soi_r_attitude_4 & soi_r_attitude_5
Observations:	1462
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.85
Omega (hierarchical):	0.06
Revelle’s Omega (total):	0.85
Greatest Lower Bound (GLB):	0.84
Coefficient H:	0.85
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.87]
Coefficient Alpha	[0.84; 0.86]

Estimates assuming ordinal level


Ordinal Omega (total):	0.89
Ordinal Omega (hierarch.):	0.89
Ordinal Coefficient Alpha:	0.89

Confidence intervals


Ordinal Omega (total):	[0.88; 0.9]
Ordinal Coefficient Alpha	[0.88; 0.9]

Eigen values

2.314, 0.352 & 0.333

Factor analysis (reproducing only shared variance)

	ML1
soi_r_attitude_6r	0.822
soi_r_attitude_4	0.802
soi_r_attitude_5	0.809

Component analysis (reproducing full covariance matrix)

	PC1
soi_r_attitude_6r	0.882
soi_r_attitude_4	0.875
soi_r_attitude_5	0.878

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
soi_r_attitude_6r	3.52735978112175	4	1.97426804158462	1.40508648900508	3	0.0367476330848067	1	2	5	5	-0.530423406851316	-1.0613856360851	0.124829001367989	1462	1462
soi_r_attitude_4	3.56497948016416	4	1.88044281272033	1.37129238775701	3	0.0358638061867387	1	2	5	5	-0.528465357879277	-1.00413248783396	0.114569083447332	1462	1462
soi_r_attitude_5	2.9015047879617	3	2.12307781619883	1.45707852094485	2	0.0381073957243358	1	1	4	5	0.0704432848153881	-1.39044667493889	0.106475148198814	1462	1462

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
soi_r_attitude_6r	Ich möchte nicht eher Sex mit jemandem haben, solange ich mir nicht sicher bin, dass es sich um eine ernste Langzeitbeziehung handelt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.527	1.405	6	▃▃▁▃▁▆▁▇
soi_r_attitude_4	Ich finde, Sex ohne Liebe ist ok.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.565	1.371	6	▂▃▁▃▁▅▁▇
soi_r_attitude_5	Ich könnte mir vorstellen, dass ich “unverbindlichen” Sex mit verschiedenen Personen genieße und mich dabei wohl fühle.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.901	1.457	6	▇▇▁▅▁▇▁▆

Scale: bfi_consc

Overview

Reliability: ω_ordinal [95% CI] = 0.85 [0.84;0.86].

Missing: 93.

Likert plot of scale bfi_consc items

Distribution of scale bfi_consc

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	bfi_consc_2r, bfi_consc_3, bfi_consc_1, bfi_consc_9r, bfi_consc_4r, bfi_consc_5, bfi_consc_6, bfi_consc_7 & bfi_consc_8r
Observations:	1419
Positive correlations:	36
Number of correlations:	36
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.81
Omega (hierarchical):	0.70
Revelle’s Omega (total):	0.85
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.83
Coefficient Alpha:	0.81

Confidence intervals


Omega (total):	[0.8; 0.83]
Coefficient Alpha	[0.8; 0.83]

Estimates assuming ordinal level


Ordinal Omega (total):	0.85
Ordinal Omega (hierarch.):	0.85
Ordinal Coefficient Alpha:	0.85

Confidence intervals


Ordinal Omega (total):	[0.84; 0.86]
Ordinal Coefficient Alpha	[0.83; 0.86]

Eigen values

3.72, 0.942, 0.86, 0.733, 0.659, 0.622, 0.539, 0.499 & 0.426

Factor analysis (reproducing only shared variance)

	ML1
bfi_consc_2r	0.415
bfi_consc_3	0.637
bfi_consc_1	0.668
bfi_consc_9r	0.544
bfi_consc_4r	0.595
bfi_consc_5	0.618
bfi_consc_6	0.609
bfi_consc_7	0.577
bfi_consc_8r	0.563

Component analysis (reproducing full covariance matrix)

	PC1
bfi_consc_2r	0.485
bfi_consc_3	0.685
bfi_consc_1	0.710
bfi_consc_9r	0.612
bfi_consc_4r	0.663
bfi_consc_5	0.672
bfi_consc_6	0.664
bfi_consc_7	0.636
bfi_consc_8r	0.632

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
bfi_consc_2r	3.55109231853418	4	1.16011693011726	1.07708724350317	1	0.0285929973897504	1	3	5	5	-0.357876114899703	-0.760856616409921	0.114164904862579	1419	1419
bfi_consc_3	4.20577871740662	4	0.6670751865425	0.816746708926642	1	0.0216818430050954	1	3	5	5	-0.954410659665551	0.815192630283469	0.205778717406624	1419	1419
bfi_consc_1	4.02818886539817	4	0.694550384615002	0.833396895011616	1	0.0221238487294582	1	3	5	5	-0.689722406928276	0.20149625499385	0.151515151515152	1419	1419
bfi_consc_9r	2.90486257928118	3	1.73494812990336	1.31717429746536	2	0.0349664908543339	1	2	4	5	0.0977724687147142	-1.1458240895515	0.108527131782946	1419	1419
bfi_consc_4r	2.94291754756871	3	1.37544169347889	1.17279226356541	2	0.031133639668574	1	2	4	5	0.076728663360034	-0.885716708085572	0.136363636363636	1419	1419
bfi_consc_5	3.5877378435518	4	0.995646430520311	0.997820840892949	1	0.0264887444087594	1	3	5	5	-0.409055865658888	-0.423495355615039	0.134249471458774	1419	1419
bfi_consc_6	3.71952078928823	4	0.922686371041408	0.960565651603995	1	0.0254997460369756	1	3	5	5	-0.519344286595407	-0.169353461055322	0.126849894291755	1419	1419
bfi_consc_7	3.78999295278365	4	0.892396262291627	0.944667275971613	1	0.0250776983192072	1	3	5	5	-0.540847531162739	-0.100095392852032	0.126849894291755	1419	1419
bfi_consc_8r	3.12544045102185	3	1.31006459782659	1.14458053356965	2	0.0303847143359283	1	2	4	5	-0.159133929098284	-0.831804268254366	0.136715997181113	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
bfi_consc_2r	Ich sehe mich selbst als jemanden, der etwas achtlos sein kann.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	3.559	1.0744	6	▁▃▁▅▁▇▁▅
bfi_consc_3	Ich sehe mich selbst als jemanden, der zuverlässig ist und gewissenhaft.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	4.198	0.8225	6	▁▁▁▂▁▇▁▇
bfi_consc_1	Ich sehe mich selbst als jemanden, der Aufgaben gründlich erledigt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	4	5	4.019	0.8475	6	▁▁▁▃▁▇▁▅
bfi_consc_9r	Ich sehe mich selbst als jemanden, der dazu neigt, unordentlich zu sein.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.905	1.3206	6	▆▇▁▇▁▇▁▅
bfi_consc_4r	Ich sehe mich selbst als jemanden, der bequem ist und zur Faulheit neigt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.942	1.1755	6	▃▇▁▇▁▇▁▃
bfi_consc_5	Ich sehe mich selbst als jemanden, der nicht aufgibt, ehe die Aufgabe erledigt ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.591	1.0006	6	▁▂▁▆▁▇▁▃
bfi_consc_6	Ich sehe mich selbst als jemanden, der tüchtig ist und flott arbeitet.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.720	0.9606	6	▁▂▁▅▁▇▁▅
bfi_consc_7	Ich sehe mich selbst als jemanden, der Pläne macht und diese auch durchführt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	4	5	3.790	0.9447	6	▁▂▁▅▁▇▁▅
bfi_consc_8r	Ich sehe mich selbst als jemanden, der leicht ablenkbar ist, nicht bei der Sache bleibt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	3.125	1.1446	6	▂▆▁▇▁▇▁▃

Scale: asendorpf_shyness

Overview

Reliability: ω_ordinal [95% CI] = 0.88 [0.87;0.89].

Missing: 93.

Likert plot of scale asendorpf_shyness items

Distribution of scale asendorpf_shyness

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	asendorpf_shyness_4r, asendorpf_shyness_2, asendorpf_shyness_5, asendorpf_shyness_3r & asendorpf_shyness_1
Observations:	1419
Positive correlations:	10
Number of correlations:	10
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.86
Omega (hierarchical):	0.81
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.89
Coefficient H:	0.88
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.87]
Coefficient Alpha	[0.84; 0.87]

Estimates assuming ordinal level


Ordinal Omega (total):	0.88
Ordinal Omega (hierarch.):	0.88
Ordinal Coefficient Alpha:	0.88

Confidence intervals


Ordinal Omega (total):	[0.87; 0.89]
Ordinal Coefficient Alpha	[0.87; 0.89]

Eigen values

3.205, 0.677, 0.526, 0.334 & 0.259

Factor analysis (reproducing only shared variance)

	ML1
asendorpf_shyness_4r	0.811
asendorpf_shyness_2	0.716
asendorpf_shyness_5	0.533
asendorpf_shyness_3r	0.849
asendorpf_shyness_1	0.785

Component analysis (reproducing full covariance matrix)

	PC1
asendorpf_shyness_4r	0.833
asendorpf_shyness_2	0.796
asendorpf_shyness_5	0.646
asendorpf_shyness_3r	0.860
asendorpf_shyness_1	0.848

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
asendorpf_shyness_4r	2.68217054263566	3	1.44545762674801	1.20227186058229	2	0.0319162225518445	1	2	4	5	0.331962201553692	-0.815730854463806	0.12262156448203	1419	1419
asendorpf_shyness_2	2.6800563777308	3	1.11195034942862	1.05449056393532	1	0.0279931325191952	1	2	4	5	0.261324523126014	-0.601816507955876	0.149048625792812	1419	1419
asendorpf_shyness_5	2.64411557434813	2	1.58905385405205	1.26057679419068	2	0.0334640199327251	1	1	4	5	0.337283548551323	-0.941045544066679	0.109936575052854	1419	1419
asendorpf_shyness_3r	2.5968992248062	2	1.25347415838445	1.11958660155633	1	0.0297212105788025	1	1	3	5	0.321254689711459	-0.747680262601273	0.122269203664553	1419	1419
asendorpf_shyness_1	2.72374911909796	3	1.31291230936982	1.14582385617067	2	0.0304177203158058	1	2	4	5	0.205058319475354	-0.764741164593884	0.145525017618041	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
asendorpf_shyness_4r	Ich finde es leicht, mit Fremden in Kontakt zu kommen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.672	1.196	6	▅▇▁▆▁▅▁▂
asendorpf_shyness_2	Ich fühle mich anderen gegenüber gehemmt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	2.672	1.055	6	▃▇▁▇▁▅▁▁
asendorpf_shyness_5	Ich fühle mich auf Parties und in anderen größeren Gruppen unwohl.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	2	5	2.643	1.257	6	▆▇▁▆▁▅▁▂
asendorpf_shyness_3r	Ich gehe ungezwungen auf andere Menschen zu.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	2	5	2.596	1.117	6	▃▇▁▆▁▅▁▁
asendorpf_shyness_1	Ich fühle mich in Gegenwart anderer schüchtern.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	2.724	1.146	6	▅▇▁▇▁▅▁▂

Scale: bfi_neuro

Overview

Reliability: ω_ordinal [95% CI] = 0.87 [0.86;0.88].

Missing: 93.

Likert plot of scale bfi_neuro items

Distribution of scale bfi_neuro

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	bfi_neuro_2r, bfi_neuro_1, bfi_neuro_3, bfi_neuro_4, bfi_neuro_5r, bfi_neuro_8, bfi_neuro_6r & bfi_neuro_7
Observations:	1419
Positive correlations:	28
Number of correlations:	28
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.85
Omega (hierarchical):	0.72
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.89
Coefficient H:	0.86
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.86]
Coefficient Alpha	[0.84; 0.86]

Estimates assuming ordinal level


Ordinal Omega (total):	0.87
Ordinal Omega (hierarch.):	0.86
Ordinal Coefficient Alpha:	0.87

Confidence intervals


Ordinal Omega (total):	[0.86; 0.88]
Ordinal Coefficient Alpha	[0.86; 0.88]

Eigen values

3.913, 0.989, 0.761, 0.565, 0.549, 0.447, 0.415 & 0.361

Factor analysis (reproducing only shared variance)

	ML1
bfi_neuro_2r	0.725
bfi_neuro_1	0.527
bfi_neuro_3	0.690
bfi_neuro_4	0.560
bfi_neuro_5r	0.718
bfi_neuro_8	0.573
bfi_neuro_6r	0.725
bfi_neuro_7	0.611

Component analysis (reproducing full covariance matrix)

	PC1
bfi_neuro_2r	0.747
bfi_neuro_1	0.621
bfi_neuro_3	0.748
bfi_neuro_4	0.648
bfi_neuro_5r	0.741
bfi_neuro_8	0.651
bfi_neuro_6r	0.741
bfi_neuro_7	0.685

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
bfi_neuro_2r	3.22128259337562	3	1.24154955266577	1.11424842502279	2	0.0295795001754808	1	2	4	5	-0.140942561537846	-0.809411519300068	0.13953488372093	1419	1419
bfi_neuro_1	2.26708949964764	2	1.27346479522817	1.12847897420739	2	0.0299572727822444	1	1	3	5	0.61774597722199	-0.428104565751207	0.151867512332629	1419	1419
bfi_neuro_3	2.88794926004228	3	1.18983352069586	1.09079490313067	2	0.0289568890599126	1	2	4	5	0.121966287615833	-0.804177049117325	0.139182522903453	1419	1419
bfi_neuro_4	3.66243833685694	4	1.24492804185788	1.11576343454062	2	0.0296197185175418	1	3	5	5	-0.517933448329891	-0.610939951276621	0.132135306553911	1419	1419
bfi_neuro_5r	2.89006342494715	3	1.14023264759644	1.06781676686426	2	0.0283468978133819	1	2	4	5	0.125945433739933	-0.683648640706795	0.150105708245243	1419	1419
bfi_neuro_8	3.15151515151515	3	1.4290721032611	1.19543803823582	2	0.0317348078468673	1	2	4	5	-0.130231955048835	-0.949934787075819	0.123326286116984	1419	1419
bfi_neuro_6r	2.90909090909091	3	1.146172586229	1.0705945013071	2	0.0284206372009316	1	2	4	5	0.108958996073248	-0.700585148920632	0.147991543340381	1419	1419
bfi_neuro_7	2.93657505285412	3	1.31473325441246	1.14661818161603	2	0.0304388069506378	1	2	4	5	0.124186092821193	-0.84458445376297	0.139182522903453	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
bfi_neuro_2r	Ich sehe mich selbst als jemanden, der entspannt ist, sich durch Stress nicht aus der Ruhe bringen lässt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	3	5	3.222	1.111	6	▂▆▁▇▁▇▁▃
bfi_neuro_1	Ich sehe mich selbst als jemanden, der deprimiert, niedergeschlagen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	2	5	2.269	1.123	6	▇▇▁▆▁▃▁▁
bfi_neuro_3	Ich sehe mich selbst als jemanden, der leicht angespannt reagiert.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.889	1.088	6	▂▇▁▇▁▆▁▂
bfi_neuro_4	Ich sehe mich selbst als jemanden, der sich viele Sorgen macht.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	4	5	3.660	1.115	6	▁▃▁▅▁▇▁▆
bfi_neuro_5r	Ich sehe mich selbst als jemanden, der nicht leicht aus der Fassung zu bringen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.894	1.065	6	▂▇▁▇▁▆▁▂
bfi_neuro_8	Ich sehe mich selbst als jemanden, der launisch sein kann, schwankende Stimmungen hat.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	3.152	1.197	6	▂▆▁▇▁▇▁▃
bfi_neuro_6r	Ich sehe mich selbst als jemanden, der ruhig bleibt, selbst in angespannten Situationen ausgeglichen ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	2.909	1.071	6	▂▇▁▇▁▆▁▂
bfi_neuro_7	Ich sehe mich selbst als jemanden, der leicht nervös und unsicher wird.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	2.937	1.147	6	▃▇▁▇▁▆▁▃

Scale: pvd_germ_aversion

Overview

Reliability: ω_ordinal [95% CI] = 0.67 [0.65;0.7].

Missing: 93.

Likert plot of scale pvd_germ_aversion items

Distribution of scale pvd_germ_aversion

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	pvd_germ_aversion_2, pvd_germ_aversion_3R, pvd_germ_aversion_1 & pvd_germ_aversion_4R
Observations:	1419
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.59
Omega (hierarchical):	0.56
Revelle’s Omega (total):	0.61
Greatest Lower Bound (GLB):	0.60
Coefficient H:	0.62
Coefficient Alpha:	0.58

Confidence intervals


Omega (total):	[0.55; 0.62]
Coefficient Alpha	[0.54; 0.61]

Estimates assuming ordinal level


Ordinal Omega (total):	0.67
Ordinal Omega (hierarch.):	0.67
Ordinal Coefficient Alpha:	0.67

Confidence intervals


Ordinal Omega (total):	[0.65; 0.7]
Ordinal Coefficient Alpha	[0.64; 0.69]

Eigen values

1.808, 0.848, 0.677 & 0.667

Factor analysis (reproducing only shared variance)

	ML1
pvd_germ_aversion_2	0.556
pvd_germ_aversion_3R	0.566
pvd_germ_aversion_1	0.590
pvd_germ_aversion_4R	0.360

Component analysis (reproducing full covariance matrix)

	PC1
pvd_germ_aversion_2	0.702
pvd_germ_aversion_3R	0.707
pvd_germ_aversion_1	0.723
pvd_germ_aversion_4R	0.541

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
pvd_germ_aversion_2	2.83298097251586	3	2.03625986635138	1.42697577637162	2	0.0378813460981358	1	1	4	5	0.155639071211968	-1.32319145942006	0.113460183227625	1419	1419
pvd_germ_aversion_3R	1.60887949260042	1	1.10855297488945	1.05287842360334	1	0.0279503356848791	1	NA	2	5	1.86259484414591	2.66040258046728	0.0937279774489077	1419	1419
pvd_germ_aversion_1	1.70754052149401	1	1.00820121045135	1.00409223204412	1	0.0266552284813331	1	NA	2	5	1.47672565774217	1.61387940238512	0.121564482029598	1419	1419
pvd_germ_aversion_4R	2.7815362931642	3	1.50654178482433	1.22741263836753	2	0.0325836245640078	1	2	4	5	0.204282128432199	-0.975514775224748	0.115574348132488	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
pvd_germ_aversion_2	Ich mag es nicht mit einem Stift zu schreiben, an dem offensichtlich eine andere Person gekaut hat.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.842	1.426	6	▇▇▁▆▁▆▁▆
pvd_germ_aversion_3R	Es macht mir nichts aus, mit einem Freund eine Wasserflasche zu teilen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	1	5	1.616	1.061	6	▇▂▁▁▁▁▁▁
pvd_germ_aversion_1	Am liebsten wasche ich meine Hände direkt, nachdem ich jemandem die Hände geschüttelt habe.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	1	5	1.717	1.012	6	▇▃▁▂▁▁▁▁
pvd_germ_aversion_4R	Es macht mir keine Sorgen, von kranken Menschen umgeben zu sein.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	3	5	2.781	1.227	6	▅▇▁▆▁▆▁▂

Scale: pvd_infectability

Overview

Reliability: ω_ordinal [95% CI] = 0.87 [0.86;0.88].

Missing: 93.

Likert plot of scale pvd_infectability items

Distribution of scale pvd_infectability

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	pvd_infectability_1, pvd_infectability_3R & pvd_infectability_2
Observations:	1419
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.84
Omega (hierarchical):	0.00
Revelle’s Omega (total):	0.84
Greatest Lower Bound (GLB):	0.85
Coefficient H:	0.85
Coefficient Alpha:	0.84

Confidence intervals


Omega (total):	[0.83; 0.85]
Coefficient Alpha	[0.82; 0.85]

Estimates assuming ordinal level


Ordinal Omega (total):	0.87
Ordinal Omega (hierarch.):	0.87
Ordinal Coefficient Alpha:	0.87

Confidence intervals


Ordinal Omega (total):	[0.86; 0.88]
Ordinal Coefficient Alpha	[0.86; 0.88]

Eigen values

2.264, 0.413 & 0.323

Factor analysis (reproducing only shared variance)

	ML1
pvd_infectability_1	0.853
pvd_infectability_3R	0.762
pvd_infectability_2	0.770

Component analysis (reproducing full covariance matrix)

	PC1
pvd_infectability_1	0.888
pvd_infectability_3R	0.857
pvd_infectability_2	0.860

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
pvd_infectability_1	2.23255813953488	2	1.37324105356381	1.17185368266	2	0.031108723542661	1	1	3	5	0.738848789551805	-0.346777885499556	0.162085976039464	1419	1419
pvd_infectability_3R	2.71035940803383	3	1.22846101318893	1.10835960463603	1	0.0294231720535361	1	2	4	5	0.238125425211416	-0.627024708541569	0.151162790697674	1419	1419
pvd_infectability_2	2.17970401691332	2	1.13199963024478	1.0639547124971	2	0.0282443734254036	1	1	3	5	0.724390880896979	-0.11118863126463	0.15292459478506	1419	1419

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
pvd_infectability_1	Ich bin generell sehr anfällig für Erkältungen, Grippen und andere Infektionen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	5	50	0.9669	1	2	5	2.235	1.168	6	▇▇▁▅▁▃▁▁
pvd_infectability_3R	Mein Immunsystem schützt mich vor den meisten Krankheiten, die andere Leute bekommen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	28	73	0.9517	1	3	5	2.712	1.106	6	▃▇▁▇▁▅▁▂
pvd_infectability_2	Wenn eine Krankheit „gerade umgeht“, bekomme ich sie bestimmt auch.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	55	93	0.9385	1	2	5	2.180	1.064	6	▇▇▁▅▁▂▁▁

Scale: spms_partner

Overview

Reliability: ω_ordinal [95% CI] = 0.86 [0.84;0.87].

Missing: 570.

Likert plot of scale spms_partner items

Distribution of scale spms_partner

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	spms_partner_1, spms_partner_2 & spms_partner_3R
Observations:	942
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.82
Omega (hierarchical):	0.04
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.84
Coefficient H:	0.84
Coefficient Alpha:	0.82

Confidence intervals


Omega (total):	[0.8; 0.84]
Coefficient Alpha	[0.8; 0.84]

Estimates assuming ordinal level


Ordinal Omega (total):	0.86
Ordinal Omega (hierarch.):	0.85
Ordinal Coefficient Alpha:	0.85

Confidence intervals


Ordinal Omega (total):	[0.84; 0.87]
Ordinal Coefficient Alpha	[0.84; 0.87]

Eigen values

2.211, 0.473 & 0.316

Factor analysis (reproducing only shared variance)

	ML1
spms_partner_1	0.782
spms_partner_2	0.865
spms_partner_3R	0.691

Component analysis (reproducing full covariance matrix)

	PC1
spms_partner_1	0.863
spms_partner_2	0.888
spms_partner_3R	0.823

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
spms_partner_1	3.64012738853503	4	0.980874797782546	0.990391234706036	1	0.0322686901318675	1	3	5	5	-0.375584802582975	-0.383073123912641	0.150743099787686	942	942
spms_partner_2	3.38428874734607	3	0.963748643422659	0.981707004876026	1	0.0319857426343549	1	2	4	5	-0.133924268400622	-0.401762661093455	0.154458598726115	942	942
spms_partner_3R	3.25796178343949	3	1.19055822170479	1.09112704196385	1	0.0355508400900614	1	2	4	5	-0.20508575201181	-0.605903805394255	0.14968152866242	942	942

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
spms_partner_1	Frauen bemerken meinen Partner.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 82 </td> <td style="text-align:right;"> 570 </td> <td style="text-align:right;"> 0.623 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.640 </td> <td style="text-align:right;"> 0.9904 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▂▁▆▁▇▁▅ </td> </tr> <tr> <td style="text-align:left;"> spms_partner_2 </td> <td style="text-align:left;"> Frauen fühlen sich zu meinem Partner hingezogen. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		82	570	0.623	1	3	5	3.384	0.9817	7	▁▃▁▇▁▆▁▃
spms_partner_3R	Mein Partner bekommt von Frauen nur selten Komplimente.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo$hetero_relationship == 1		82	570	0.623	1	3	5	3.258	1.0911	7	▂▅▁▇▁▇▁▃

Scale: spms_self

Overview

Reliability: ω_ordinal [95% CI] = 0.89 [0.88;0.9].

Missing: 99.

Likert plot of scale spms_self items

Distribution of scale spms_self

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	spms_self_1, spms_self_2 & spms_self_3R
Observations:	1413
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.85
Omega (hierarchical):	0.04
Revelle’s Omega (total):	0.86
Greatest Lower Bound (GLB):	0.87
Coefficient H:	0.87
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.87]
Coefficient Alpha	[0.84; 0.87]

Estimates assuming ordinal level


Ordinal Omega (total):	0.89
Ordinal Omega (hierarch.):	0.89
Ordinal Coefficient Alpha:	0.89

Confidence intervals


Ordinal Omega (total):	[0.88; 0.9]
Ordinal Coefficient Alpha	[0.88; 0.9]

Eigen values

2.329, 0.4 & 0.271

Factor analysis (reproducing only shared variance)

	ML1
spms_self_1	0.821
spms_self_2	0.881
spms_self_3R	0.746

Component analysis (reproducing full covariance matrix)

	PC1
spms_self_1	0.885
spms_self_2	0.903
spms_self_3R	0.854

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
spms_self_1	3.6135881104034	4	1.06021183305967	1.02966588418752	1	0.0273920945851273	1	3	5	5	-0.604890632650613	-0.0677967009074301	0.128096249115357	1413	1413
spms_self_2	3.4069355980184	3	1.03896036199676	1.01929405080024	1	0.0271161737786514	1	2	4	5	-0.371789608268124	-0.331087106000438	0.159235668789809	1413	1413
spms_self_3R	3.47487615003539	4	1.33453123465032	1.15521912841258	1	0.0307321745024066	1	3	5	5	-0.551497243292905	-0.486209335381379	0.114295824486907	1413	1413

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
spms_self_1	Männer bemerken mich.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	4	5	3.614	1.030	6	▁▂▁▅▁▇▁▃
spms_self_2	Männer fühlen sich zu mir hingezogen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	3	5	3.407	1.019	6	▁▃▁▇▁▇▁▃
spms_self_3R	Ich bekomme von Männern nur selten Komplimente.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	4	5	3.475	1.155	6	▂▃▁▅▁▇▁▃

Scale: relationship_satisfaction

Overview

Reliability: ω_ordinal [95% CI] = 0.91 [0.9;0.92].

Missing: 572.

Likert plot of scale relationship_satisfaction items

Distribution of scale relationship_satisfaction

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	relationship_problems_R, relationship_satisfaction_overall, relationship_conflict_R, relationship_satisfaction_2 & relationship_satisfaction_3
Observations:	940
Positive correlations:	10
Number of correlations:	10
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.87
Omega (hierarchical):	0.83
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.93
Coefficient H:	0.92
Coefficient Alpha:	0.87

Confidence intervals


Omega (total):	[0.86; 0.88]
Coefficient Alpha	[0.86; 0.89]

Estimates assuming ordinal level


Ordinal Omega (total):	0.91
Ordinal Omega (hierarch.):	0.89
Ordinal Coefficient Alpha:	0.91

Confidence intervals


Ordinal Omega (total):	[0.9; 0.92]
Ordinal Coefficient Alpha	[0.9; 0.92]

Eigen values

3.394, 0.775, 0.358, 0.288 & 0.185

Factor analysis (reproducing only shared variance)

	ML1
relationship_problems_R	0.743
relationship_satisfaction_overall	0.902
relationship_conflict_R	0.543
relationship_satisfaction_2	0.758
relationship_satisfaction_3	0.883

Component analysis (reproducing full covariance matrix)

	PC1
relationship_problems_R	0.846
relationship_satisfaction_overall	0.888
relationship_conflict_R	0.687
relationship_satisfaction_2	0.804
relationship_satisfaction_3	0.878

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
relationship_problems_R	3.86276595744681	4	1.34536401332336	1.15989827714475	2	0.0378317104033922	1	3	5	5	-0.900347569518517	0.000429579103411686	0.162765957446809	940	940
relationship_satisfaction_overall	4.31170212765957	5	0.97089592821698	0.985340513841271	1	0.0321382639347783	1	4	NA	5	-1.49931275549617	1.71392745421107	0.122872340425532	940	940
relationship_conflict_R	3.68936170212766	4	1.32832121088528	1.15252818225208	2	0.0375913244134142	1	3	5	5	-0.636781319254214	-0.429155240165173	0.143085106382979	940	940
relationship_satisfaction_2	3.97127659574468	4	1.10141050914282	1.04948106659569	2	0.0342302980939217	1	3	5	5	-1.0007097688853	0.451406982452771	0.182446808510638	940	940
relationship_satisfaction_3	4.23191489361702	4.5	0.898234880928104	0.947752542031992	1	0.0309122794737616	1	4	5	5	-1.21421240117257	0.951124684814117	0.15531914893617	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
relationship_problems_R	Es gibt viele Probleme in meiner Beziehung.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4.0 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.863 </td> <td style="text-align:right;"> 1.1599 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▂▁▃▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> relationship_satisfaction_overall </td> <td style="text-align:left;"> Ich bin im Großen und Ganzen zufrieden mit meiner Beziehung. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	5.0	5	4.312	0.9853	7	▁▁▁▂▁▃▁▇
relationship_conflict_R	Es gibt oft Streit/Meinungsverschiedenheiten in meiner Partnerschaft.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4.0 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.689 </td> <td style="text-align:right;"> 1.1525 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▃▁▅▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> relationship_satisfaction_2 </td> <td style="text-align:left;"> In unserer Beziehung werden meine Bedürfnisse (z.B. nach Intimität, Gemeinsamkeit, etc.) erfüllt. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	4.0	5	3.971	1.0495	7	▁▂▁▃▁▇▁▇
relationship_satisfaction_3	Unsere Beziehung macht mich sehr glücklich.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo$hetero_relationship == 1	119	572	0.6217	1	4.5	5	4.232	0.9478	7	▁▁▁▂▁▅▁▇

Scale: alternatives

Overview

Reliability: ω_ordinal [95% CI] = 0.8 [0.78;0.82].

Missing: 572.

Likert plot of scale alternatives items

Distribution of scale alternatives

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	alternatives_1, alternatives_2, alternatives_3, alternatives_4, alternatives_5 & alternatives_6
Observations:	940
Positive correlations:	15
Number of correlations:	15
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.77
Omega (hierarchical):	0.70
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.77
Coefficient H:	0.79
Coefficient Alpha:	0.76

Confidence intervals


Omega (total):	[0.74; 0.79]
Coefficient Alpha	[0.74; 0.79]

Estimates assuming ordinal level


Ordinal Omega (total):	0.8
Ordinal Omega (hierarch.):	0.8
Ordinal Coefficient Alpha:	0.8

Confidence intervals


Ordinal Omega (total):	[0.78; 0.82]
Ordinal Coefficient Alpha	[0.78; 0.82]

Eigen values

2.76, 0.851, 0.778, 0.582, 0.569 & 0.461

Factor analysis (reproducing only shared variance)

	ML1
alternatives_1	0.747
alternatives_2	0.590
alternatives_3	0.518
alternatives_4	0.562
alternatives_5	0.658
alternatives_6	0.473

Component analysis (reproducing full covariance matrix)

	PC1
alternatives_1	0.782
alternatives_2	0.677
alternatives_3	0.608
alternatives_4	0.662
alternatives_5	0.736
alternatives_6	0.584

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
alternatives_1	2.84042553191489	3	1.70826818933678	1.30700734096514	2	0.0426298790099248	1	2	4	5	0.145178500616055	-1.13053745866452	0.107446808510638	940	940
alternatives_2	2.37340425531915	2	1.47170937846963	1.21314029628466	2	0.0395682735909426	1	1	3	5	0.592976300318238	-0.600252158334668	0.14468085106383	940	940
alternatives_3	2.27872340425532	2	1.56014320349852	1.24905692564371	2	0.0407397448719609	1	1	4	5	0.690425659216733	-0.633597346881776	0.148936170212766	940	940
alternatives_4	2.21595744680851	2	1.24724242630231	1.11680008340898	2	0.0364260023198053	1	1	3	5	0.775968210024259	-0.100470206751446	0.152659574468085	940	940
alternatives_5	3.47340425531915	4	1.58502141254843	1.25897633518205	2	0.0410632803374597	1	2	5	5	-0.43560043704709	-0.836934296914847	0.128723404255319	940	940
alternatives_6	2.68085106382979	3	1.60410577119163	1.2665329728008	2	0.0413097506802896	1	2	4	5	0.250420452627273	-0.946842805704418	0.118617021276596	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
alternatives_1	Ich finde auch andere Personen als meinen Partner, mit denen ich eine Beziehung haben könnte, sehr anziehend.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 3 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 2.840 </td> <td style="text-align:right;"> 1.307 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▆▇▁▆▁▆▁▃ </td> </tr> <tr> <td style="text-align:left;"> alternatives_2 </td> <td style="text-align:left;"> Die Alternativen zu unserer Beziehung (z.B. andere Partnerschaft, mit Freunden zusammen sein, allein sein) sind für mich sehr reizvoll. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	2	5	2.373	1.213	7	▇▇▁▆▁▃▁▂
alternatives_3	Ich flirte mit Männern, ohne dass diese wissen, dass ich in einer Partnerschaft bin.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 2.279 </td> <td style="text-align:right;"> 1.249 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▇▇▁▃▁▃▁▂ </td> </tr> <tr> <td style="text-align:left;"> alternatives_4 </td> <td style="text-align:left;"> Meine Bedürfnisse (z.B. nach Intimität, Gemeinsamkeit, etc.) könnten mit Leichtigkeit in einer anderen Beziehung erfüllt werden. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	2	5	2.216	1.117	7	▇▇▁▅▁▂▁▁
alternatives_5	Mir ist sehr bewusst, dass es “da draußen” noch viele andere attraktive potentielle Partner für mich gibt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.473 </td> <td style="text-align:right;"> 1.259 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▂▅▁▆▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> alternatives_6 </td> <td style="text-align:left;"> Es wäre leicht für mich, einen Partner für eine neue Beziehung zu finden. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	3	5	2.681	1.266	7	▆▇▁▇▁▅▁▃

Scale: investment

Overview

Reliability: ω_ordinal [95% CI] = 0.67 [0.61;0.73].

Missing: 572.

Likert plot of scale investment items

Distribution of scale investment

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	investment_1, investment_2 & investment_3
Observations:	940
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.65
Omega (hierarchical):	0.03
Revelle’s Omega (total):	0.62
Greatest Lower Bound (GLB):	0.65
Coefficient H:	0.94
Coefficient Alpha:	0.55

Confidence intervals


Omega (total):	[0.58; 0.72]
Coefficient Alpha	[0.5; 0.6]

Estimates assuming ordinal level


Ordinal Omega (total):	0.67
Ordinal Omega (hierarch.):	0.67
Ordinal Coefficient Alpha:	0.58

Confidence intervals


Ordinal Omega (total):	[0.61; 0.73]
Ordinal Coefficient Alpha	[0.53; 0.63]

Eigen values

1.587, 0.909 & 0.503

Factor analysis (reproducing only shared variance)

	ML1
investment_1	0.969
investment_2	0.498
investment_3	0.238

Component analysis (reproducing full covariance matrix)

	PC1
investment_1	0.845
investment_2	0.794
investment_3	0.493

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
investment_1	3.47553191489362	4	1.50632293295267	1.22732348341937	1	0.0400308781476099	1	3	5	5	-0.410967710066757	-0.807468928311765	0.123404255319149	940	940
investment_2	2.73404255319149	3	1.8013957809349	1.34216086254029	2	0.0437764604594327	1	2	4	5	0.265418861280402	-1.1325581752615	0.111702127659574	940	940
investment_3	3.86276595744681	4	0.964107357306324	0.981889686933478	2	0.0320257103714182	1	3	5	5	-0.662740764178549	-0.0696375405945993	0.145744680851064	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
investment_1	Ich habe viel in unsere Beziehung hineingesteckt, das ich verlieren würde, wenn die Beziehung zu Ende wäre.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.475 </td> <td style="text-align:right;"> 1.2273 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▂▅▁▇▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> investment_2 </td> <td style="text-align:left;"> Viele Aspekte meines Lebens sind so eng mit meinem Partner verbunden (z.B. Freizeitgestaltung, gemeinsamer Freundes- und Bekanntenkreis), dass ich all dies verlieren würde, wenn wir uns trennen würden. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		119	572	0.6217	1	3	5	2.734	1.3422	7	▇▇▁▆▁▆▁▃
investment_3	Ich investiere viel (z.B. Zeit, kleine Aufmerksamkeiten, Geschenke) in die Beziehung zu meinem Partner.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo$hetero_relationship == 1		119	572	0.6217	1	4	5	3.863	0.9819	7	▁▂▁▅▁▇▁▆

Scale: commitment

Overview

Reliability: ω_ordinal [95% CI] = 0.91 [0.9;0.92].

Missing: 572.

Likert plot of scale commitment items

Distribution of scale commitment

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	commitment_1, commitment_2 & commitment_3
Observations:	940
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.85
Omega (hierarchical):	0.01
Revelle’s Omega (total):	0.87
Greatest Lower Bound (GLB):	0.88
Coefficient H:	0.89
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.87]
Coefficient Alpha	[0.84; 0.87]

Estimates assuming ordinal level


Ordinal Omega (total):	0.91
Ordinal Omega (hierarch.):	0.91
Ordinal Coefficient Alpha:	0.91

Confidence intervals


Ordinal Omega (total):	[0.9; 0.92]
Ordinal Coefficient Alpha	[0.9; 0.92]

Eigen values

2.344, 0.4 & 0.256

Factor analysis (reproducing only shared variance)

	ML1
commitment_1	0.910
commitment_2	0.789
commitment_3	0.762

Component analysis (reproducing full covariance matrix)

	PC1
commitment_1	0.913
commitment_2	0.875
commitment_3	0.863

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
commitment_1	4.53404255319149	5	0.74750866698389	0.864585835521199	1	0.0281996806037422	1	4	NA	5	-2.03728709425677	3.94141737996045	0.0765957446808511	940	940
commitment_2	4.24148936170213	5	1.22916071873655	1.1086752088581	1	0.0361609981318263	1	4	NA	5	-1.50240467304718	1.42773363750664	0.112234042553191	940	940
commitment_3	4.35957446808511	5	1.09101579317064	1.04451701430405	1	0.0340683885606247	1	4	NA	5	-1.65276805098339	1.8579737488961	0.0888297872340426	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
commitment_1	Ich möchte, dass unsere Beziehung noch sehr lange dauert.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 4.534 </td> <td style="text-align:right;"> 0.8646 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▁▁▁▁▂▁▇ </td> </tr> <tr> <td style="text-align:left;"> commitment_2 </td> <td style="text-align:left;"> Ich orientiere mich an einer langfristigen Zukunft unserer Partnerschaft (z.B. stelle mit unser Zusammensein in einigen Jahren vor, mache Pläne für die Zukunft). </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		119	572	0.6217	1	5	5	4.242	1.1087	7	▁▁▁▂▁▃▁▇
commitment_3	Es würde mich sehr aus der Fassung bringen, wenn unsere Beziehung in nächster Zeit enden würde.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo$hetero_relationship == 1		119	572	0.6217	1	5	5	4.360	1.0445	7	▁▁▁▁▁▂▁▇

Scale: communal_strength

Overview

Reliability: ω_ordinal [95% CI] = 0.79 [0.76;0.81].

Missing: 572.

Likert plot of scale communal_strength items

Distribution of scale communal_strength

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	communal_strength_1, communal_strength_2R, communal_strength_3 & communal_strength_4
Observations:	940
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.73
Omega (hierarchical):	0.71
Revelle’s Omega (total):	0.74
Greatest Lower Bound (GLB):	0.73
Coefficient H:	0.74
Coefficient Alpha:	0.72

Confidence intervals


Omega (total):	[0.7; 0.76]
Coefficient Alpha	[0.69; 0.75]

Estimates assuming ordinal level


Ordinal Omega (total):	0.79
Ordinal Omega (hierarch.):	0.79
Ordinal Coefficient Alpha:	0.78

Confidence intervals


Ordinal Omega (total):	[0.76; 0.81]
Ordinal Coefficient Alpha	[0.76; 0.81]

Eigen values

2.191, 0.693, 0.591 & 0.525

Factor analysis (reproducing only shared variance)

	ML1
communal_strength_1	0.629
communal_strength_2R	0.618
communal_strength_3	0.719
communal_strength_4	0.555

Component analysis (reproducing full covariance matrix)

	PC1
communal_strength_1	0.744
communal_strength_2R	0.734
communal_strength_3	0.789
communal_strength_4	0.690

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
communal_strength_1	3.93723404255319	4	0.79797317200281	0.893293441150672	2	0.0291360194568548	1	3	5	5	-0.712178318949266	0.309385609614719	0.140425531914894	940	940
communal_strength_2R	4.00212765957447	4	1.04365894002221	1.02159627056005	2	0.0333207963306511	1	3	5	5	-0.977203315023973	0.489750021109989	0.181914893617021	940	940
communal_strength_3	4.21595744680851	4	0.733930392223506	0.856697374936743	1	0.0279423873891214	1	3	5	5	-1.14225612410066	1.31896448803862	0.202659574468085	940	940
communal_strength_4	4.54042553191489	5	0.446713343756373	0.668366174904425	1	0.0217997009484752	1	4	NA	5	-1.50999018697566	2.5973627499967	0.153723404255319	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
communal_strength_1	Die Bedürfnisse meines Partners zu erfüllen hat für mich hohe Priorität.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.937 </td> <td style="text-align:right;"> 0.8933 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▁▁▃▁▇▁▅ </td> </tr> <tr> <td style="text-align:left;"> communal_strength_2R </td> <td style="text-align:left;"> Für meinen Partner Opfer zu bringen widerstrebt mir. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 5. 1: trifft gar nicht zu,<br>4. 2,<br>3. 3,<br>2. 4,<br>1. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1		119	572	0.6217	1	4	5	4.002	1.0216	5	▁▁▁▃▁▇▁▇
communal_strength_3	Ich würde keine Mühen scheuen um etwas für meinen Partner zu tun.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 4.216 </td> <td style="text-align:right;"> 0.8567 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▁▁▂▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> communal_strength_4 </td> <td style="text-align:left;"> Wenn es meinem Partner einmal nicht gut geht, bin ich für ihn da, auch wenn ich dafür eigene Bedürfnisse hinten anstellen muss. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		119	572	0.6217	1	5	5	4.540	0.6684	7	▁▁▁▁▁▃▁▇

Scale: sexual_communal_strength

Overview

Reliability: ω_ordinal [95% CI] = 0.77 [0.75;0.8].

Missing: 572.

Likert plot of scale sexual_communal_strength items

Distribution of scale sexual_communal_strength

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	sexual_communal_strength_1, sexual_communal_strength_2 & sexual_communal_strength_3
Observations:	940
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.72
Omega (hierarchical):	0.03
Revelle’s Omega (total):	0.74
Greatest Lower Bound (GLB):	0.78
Coefficient H:	0.85
Coefficient Alpha:	0.69

Confidence intervals


Omega (total):	[0.69; 0.75]
Coefficient Alpha	[0.66; 0.73]

Estimates assuming ordinal level


Ordinal Omega (total):	0.77
Ordinal Omega (hierarch.):	0.77
Ordinal Coefficient Alpha:	0.74

Confidence intervals


Ordinal Omega (total):	[0.75; 0.8]
Ordinal Coefficient Alpha	[0.71; 0.77]

Eigen values

1.9, 0.774 & 0.326

Factor analysis (reproducing only shared variance)

	ML1
sexual_communal_strength_1	0.747
sexual_communal_strength_2	0.898
sexual_communal_strength_3	0.391

Component analysis (reproducing full covariance matrix)

	PC1
sexual_communal_strength_1	0.858
sexual_communal_strength_2	0.881
sexual_communal_strength_3	0.622

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
sexual_communal_strength_1	3.78085106382979	4	1.09995241655904	1.04878616340941	2	0.0342076328510988	1	3	5	5	-0.724424531754277	0.0587918022432108	0.138297872340426	940	940
sexual_communal_strength_2	3.71382978723404	4	1.03303537035778	1.01638347603539	1	0.0331507737202763	1	3	5	5	-0.618203738818791	-0.0690392029614097	0.121808510638298	940	940
sexual_communal_strength_3	2.9563829787234	3	1.3175843473138	1.14786077000384	2	0.0374390902115122	1	2	4	5	-0.0247201395190144	-0.819908165404863	0.126063829787234	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
sexual_communal_strength_1	Ich gebe mir große Mühe, um die sexuellen Bedürfnisse meines Partners zu erfüllen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.781 </td> <td style="text-align:right;"> 1.049 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▂▁▅▁▇▁▆ </td> </tr> <tr> <td style="text-align:left;"> sexual_communal_strength_2 </td> <td style="text-align:left;"> Die sexuellen Bedürfnisse meines Partners zu erfüllen hat für mich hohe Priorität. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		119	572	0.6217	1	4	5	3.714	1.016	7	▁▂▁▅▁▇▁▅
sexual_communal_strength_3	Um die sexuellen Bedürfnisse meines Partners zu erfüllen, bin ich bereit, meine eigenen sexuellen Bedürfnisse hintenan zu stellen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo$hetero_relationship == 1		119	572	0.6217	1	3	5	2.956	1.148	7	▃▆▁▇▁▇▁▂

Scale: ecr_avo

Overview

Reliability: ω_ordinal [95% CI] = 0.82 [0.81;0.84].

Missing: 572.

Likert plot of scale ecr_avo items

Distribution of scale ecr_avo

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	ecr_avo_1R, ecr_avo_2, ecr_avo_3R, ecr_avo_4, ecr_avo_5R & ecr_avo_6
Observations:	940
Positive correlations:	15
Number of correlations:	15
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.74
Omega (hierarchical):	0.52
Revelle’s Omega (total):	0.85
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.85
Coefficient Alpha:	0.76

Confidence intervals


Omega (total):	[0.72; 0.77]
Coefficient Alpha	[0.74; 0.78]

Estimates assuming ordinal level


Ordinal Omega (total):	0.82
Ordinal Omega (hierarch.):	0.77
Ordinal Coefficient Alpha:	0.83

Confidence intervals


Ordinal Omega (total):	[0.81; 0.84]
Ordinal Coefficient Alpha	[0.82; 0.85]

Eigen values

2.876, 1.232, 0.775, 0.411, 0.374 & 0.331

Factor analysis (reproducing only shared variance)

	ML2	ML1
ecr_avo_1R	0.761	0.020
ecr_avo_2	0.161	0.346
ecr_avo_3R	0.820	-0.009
ecr_avo_4	-0.016	0.983
ecr_avo_5R	0.821	-0.007
ecr_avo_6	0.061	0.550

Component analysis (reproducing full covariance matrix)

	TC1	TC2
ecr_avo_1R	0.862	-0.004
ecr_avo_2	0.065	0.620
ecr_avo_3R	0.876	0.002
ecr_avo_4	0.044	0.848
ecr_avo_5R	0.876	0.006
ecr_avo_6	-0.069	0.836

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
ecr_avo_1R	1.50744680851064	1	0.678325742641561	0.823605331843815	1	0.0268630439539108	1	NA	2	5	1.930397986018	4.03766354696944	0.123936170212766	940	940
ecr_avo_2	2.31170212765957	2	1.68016110393583	1.29621028538422	2	0.0422777178868369	1	1	4	5	0.632762497320524	-0.802013425699461	0.128723404255319	940	940
ecr_avo_3R	1.71595744680851	1	0.938403235673985	0.968712153156956	1	0.0315959066106164	1	NA	2	5	1.4527347597321	1.73497125223745	0.140957446808511	940	940
ecr_avo_4	1.53085106382979	1	0.915980105589921	0.957068495767111	1	0.0312161323811958	1	NA	2	5	1.93153436192911	3.06973820589392	0.0835106382978723	940	940
ecr_avo_5R	1.69148936170213	1	0.910044637799379	0.953962597694154	1	0.0311148291559442	1	NA	2	5	1.45367040193656	1.7098113175345	0.133510638297872	940	940
ecr_avo_6	1.53510638297872	1	0.956167720300002	0.977838289442586	1	0.0318935683554978	1	NA	2	5	1.9218078934104	2.91251270696374	0.0776595744680851	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
ecr_avo_1R	Es hilft mir, mich an meinen Partner zu wenden, wenn ich es brauche.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 1.507 </td> <td style="text-align:right;"> 0.8236 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▁▁▁▁▁ </td> </tr> <tr> <td style="text-align:left;"> ecr_avo_2 </td> <td style="text-align:left;"> Ich möchte meinem Partner nahe sein, halte mich aber trotzdem zurück. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1	119	572	0.6217	1	2	5	2.312	1.2962	5	▇▆▁▃▁▃▁▂
ecr_avo_3R	Ich wende mich oft an meinen Partner, z. B. wenn ich Trost oder Bestätigung brauche.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 1.716 </td> <td style="text-align:right;"> 0.9687 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▅▁▂▁▁▁▁ </td> </tr> <tr> <td style="text-align:left;"> ecr_avo_4 </td> <td style="text-align:left;"> Ich versuche zu vermeiden, meinem Partner zu nahe zu kommen. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1	119	572	0.6217	1	1	5	1.531	0.9571	5	▇▂▁▁▁▁▁▁
ecr_avo_5R	Ich bespreche meine Sorgen und Probleme meistens mit meinem Partner.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 1.692 </td> <td style="text-align:right;"> 0.9540 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▂▁▁▁▁ </td> </tr> <tr> <td style="text-align:left;"> ecr_avo_6 </td> <td style="text-align:left;"> Ich werde nervös, wenn mein Partner mir zu nahe kommt. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1	119	572	0.6217	1	1	5	1.535	0.9778	5	▇▂▁▁▁▁▁▁

Scale: ecr_anx

Overview

Reliability: ω_ordinal [95% CI] = 0.73 [0.7;0.76].

Missing: 572.

Likert plot of scale ecr_anx items

Distribution of scale ecr_anx

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	ecr_anx_1, ecr_anx_2, ecr_anx_3, ecr_anx_4R, ecr_anx_5 & ecr_anx_6
Observations:	940
Positive correlations:	15
Number of correlations:	15
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.69
Omega (hierarchical):	0.46
Revelle’s Omega (total):	0.80
Greatest Lower Bound (GLB):	0.79
Coefficient H:	0.88
Coefficient Alpha:	0.69

Confidence intervals


Omega (total):	[0.66; 0.72]
Coefficient Alpha	[0.66; 0.72]

Estimates assuming ordinal level


Ordinal Omega (total):	0.73
Ordinal Omega (hierarch.):	0.65
Ordinal Coefficient Alpha:	0.74

Confidence intervals


Ordinal Omega (total):	[0.7; 0.76]
Ordinal Coefficient Alpha	[0.71; 0.76]

Eigen values

2.447, 1.175, 0.892, 0.68, 0.562 & 0.245

Factor analysis (reproducing only shared variance)

	ML1	ML2
ecr_anx_1	-0.063	0.579
ecr_anx_2	0.764	0.030
ecr_anx_3	0.974	-0.035
ecr_anx_4R	0.139	0.364
ecr_anx_5	0.024	0.424
ecr_anx_6	0.447	0.297

Component analysis (reproducing full covariance matrix)

	TC1	TC2
ecr_anx_1	-0.051	0.818
ecr_anx_2	0.879	-0.051
ecr_anx_3	0.917	-0.048
ecr_anx_4R	0.311	0.410
ecr_anx_5	0.024	0.703
ecr_anx_6	0.683	0.211

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
ecr_anx_1	4.03191489361702	4	1.1342306210772	1.06500263900011	2	0.0347365559647886	1	3	5	5	-0.985990255336639	0.271177179212074	0.153191489361702	940	940
ecr_anx_2	1.72659574468085	1	1.20632066707452	1.09832630264167	1	0.0358234540293077	1	NA	2	5	1.46544080662468	1.10261844725836	0.102659574468085	940	940
ecr_anx_3	1.95425531914894	1	1.61771350236784	1.27189366787002	2	0.0414845972745261	1	NA	3	5	1.10665040325163	-0.0820193661721462	0.0973404255319149	940	940
ecr_anx_4R	2.52446808510638	2	1.69801622368749	1.30307951548917	3	0.0425017674687232	1	1	4	5	0.389096672485793	-1.0684170482348	0.137234042553191	940	940
ecr_anx_5	3.77446808510638	4	1.31436340153627	1.14645689039591	2	0.0373933007075404	1	2	5	5	-0.762197406366675	-0.28969199054538	0.155851063829787	940	940
ecr_anx_6	2.17021276595745	2	1.68345682369202	1.29748095311339	2	0.0423191624983999	1	1	4	5	0.754484100583735	-0.706806007924709	0.103191489361702	940	940

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
ecr_anx_1	Ich brauche die Bestätigung, dass mein Partner mich liebt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 4.032 </td> <td style="text-align:right;"> 1.065 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▁▁▁▃▁▆▁▇ </td> </tr> <tr> <td style="text-align:left;"> ecr_anx_2 </td> <td style="text-align:left;"> Mein Verlangen nach Nähe schreckt meinen Partner manchmal ab. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1	119	572	0.6217	1	1	5	1.727	1.098	5	▇▃▁▁▁▁▁▁
ecr_anx_3	Ich finde, mein Partner will nicht so viel Nähe wie ich.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu	s1_demo$hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 1.954 </td> <td style="text-align:right;"> 1.272 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▂▁▂▁▁ </td> </tr> <tr> <td style="text-align:left;"> ecr_anx_4R </td> <td style="text-align:left;"> Ich mache mir kaum Gedanken darüber, dass ich verlassen werden könnte. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 5. 1: trifft gar nicht zu,<br>4. 2,<br>3. 3,<br>2. 4,<br>1. 5: trifft völlig zu </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo$hetero_relationship == 1	119	572	0.6217	1	2	5	2.525	1.303	5	▇▇▁▅▁▆▁▂
ecr_anx_5	Es frustriert mich, wenn ich gerne meinen Partner bei mir hätte und er nicht da ist.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 119 </td> <td style="text-align:right;"> 572 </td> <td style="text-align:right;"> 0.6217 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.775 </td> <td style="text-align:right;"> 1.147 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▁▂▁▃▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> ecr_anx_6 </td> <td style="text-align:left;"> Ich mache mir Gedanken darüber, dass mein Partner sich nicht so um mich kümmert wie ich mich um ihn. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1	119	572	0.6217	1	2	5	2.170	1.298	7	▇▃▁▃▁▂▁▁

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	1512	0	7	7	0	NA

Scale: soi_r_desire

Overview

Reliability: ω_ordinal [95% CI] = 0.87 [0.86;0.88].

Missing: 101.

Likert plot of scale soi_r_desire items

Distribution of scale soi_r_desire

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	soi_r_desire_7, soi_r_desire_9 & soi_r_desire_8
Observations:	1411
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.84
Omega (hierarchical):	0.04
Revelle’s Omega (total):	0.84
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.86
Coefficient Alpha:	0.83

Confidence intervals


Omega (total):	[0.82; 0.85]
Coefficient Alpha	[0.81; 0.84]

Estimates assuming ordinal level


Ordinal Omega (total):	0.87
Ordinal Omega (hierarch.):	0.87
Ordinal Coefficient Alpha:	0.86

Confidence intervals


Ordinal Omega (total):	[0.86; 0.88]
Ordinal Coefficient Alpha	[0.85; 0.88]

Eigen values

2.237, 0.482 & 0.281

Factor analysis (reproducing only shared variance)

	ML1
soi_r_desire_7	0.889
soi_r_desire_9	0.674
soi_r_desire_8	0.801

Component analysis (reproducing full covariance matrix)

	PC1
soi_r_desire_7	0.898
soi_r_desire_9	0.817
soi_r_desire_8	0.874

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
soi_r_desire_7	2.96456413890858	3	1.5221476645003	1.23375348611475	2	0.0328446687302122	1	2	4	5	0.10597799331091	-1.07355022258838	0.122608079376329	1411	1411
soi_r_desire_9	2.29057406094968	2	1.29706711702882	1.13888854460338	2	0.0303191985993323	1	1	3.5	5	0.686141792861997	-0.379605850598988	0.139262934089298	1411	1411
soi_r_desire_8	2.66761162296244	2	1.17099989444637	1.08212748530216	1	0.0288081202433183	1	1	3	5	0.382946621087799	-0.596469894816504	0.128632175761871	1411	1411

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
soi_r_desire_7	Wie oft haben Sie Fantasievorstellungen, Sex mit einer Person zu haben, mit der Sie zur Zeit keine feste Beziehung führen?	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	101	0.9332	1	3	5	2.965	1.234	5	▃▇▁▆▁▆▁▃
soi_r_desire_9	Wie oft haben Sie im Alltag spontan Fantasievorstellungen, Sex mit einer fremden Person zu haben, die Sie irgendwo zufällig gesehen haben?	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	101	0.9332	1	2	5	2.291	1.139	5	▆▇▁▃▁▃▁▁
soi_r_desire_8	Sociosexual inventory-revised: Desire Subscale	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	101	0.9332	1	2	5	2.668	1.082	5	▂▇▁▆▁▃▁▁

Scale: soi_r_behavior

Overview

Reliability: ω_ordinal [95% CI] = 0.87 [0.85;0.88].

Missing: 101.

Likert plot of scale soi_r_behavior items

Distribution of scale soi_r_behavior

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	soi_r_behavior_1_discrete, soi_r_behavior_2_discrete & soi_r_behavior_3_discrete
Observations:	1411
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.87
Omega (hierarchical):	0.06
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.90
Coefficient Alpha:	0.81

Confidence intervals


Omega (total):	[0.86; 0.88]
Coefficient Alpha	[0.79; 0.83]

Estimates assuming ordinal level


Ordinal Omega (total):	0.87
Ordinal Omega (hierarch.):	0.87
Ordinal Coefficient Alpha:	0.85

Confidence intervals


Ordinal Omega (total):	[0.85; 0.88]
Ordinal Coefficient Alpha	[0.83; 0.86]

Eigen values

2.187, 0.616 & 0.197

Factor analysis (reproducing only shared variance)

	ML1
soi_r_behavior_1_discrete	0.532
soi_r_behavior_2_discrete	0.889
soi_r_behavior_3_discrete	0.903

Component analysis (reproducing full covariance matrix)

	PC1
soi_r_behavior_1_discrete	0.731
soi_r_behavior_2_discrete	0.908
soi_r_behavior_3_discrete	0.910

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
soi_r_behavior_1_discrete	2.34301913536499	2	0.784382084030741	0.885653478529126	1	0.0235776396495983	1	1	3	5	0.923128882744128	0.870286101254663	0.103827072997874	1411	1411
soi_r_behavior_2_discrete	2.43090007087172	2	1.86525727440425	1.36574421997834	2	0.0363584921787354	1	1	4	5	0.483237282976052	-1.02435724789276	0.106661941885188	1411	1411
soi_r_behavior_3_discrete	2.68674698795181	3	2.16563274374092	1.47160889632433	3	0.0391767944278865	1	1	4	5	0.247137127825115	-1.34101387686825	0.0949681077250177	1411	1411

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
soi_r_behavior_1_discrete	Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	101	0.9332	1	2	5	2.343	0.8857	5	▂▇▁▃▁▁▁▁
soi_r_behavior_2_discrete	Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	101	0.9332	1	2	5	2.431	1.3657	5	▇▅▁▅▁▃▁▂
soi_r_behavior_3_discrete	Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	101	0.9332	1	3	5	2.687	1.4716	5	▇▃▁▅▁▅▁▅

Scale: soi_r

Overview

Reliability: ω_ordinal [95% CI] = 0.88 [0.87;0.89].

Missing: 50.

Likert plot of scale soi_r items

Distribution of scale soi_r

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	soi_r_attitude_6r, soi_r_attitude_4, soi_r_attitude_5, soi_r_desire_7, soi_r_desire_9, soi_r_desire_8, soi_r_behavior_1_discrete, soi_r_behavior_2_discrete & soi_r_behavior_3_discrete
Observations:	1411
Positive correlations:	36
Number of correlations:	36
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.87
Omega (hierarchical):	0.69
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.93
Coefficient H:	0.88
Coefficient Alpha:	0.86

Confidence intervals


Omega (total):	[0.86; 0.88]
Coefficient Alpha	[0.85; 0.87]

Estimates assuming ordinal level


Ordinal Omega (total):	0.88
Ordinal Omega (hierarch.):	0.85
Ordinal Coefficient Alpha:	0.88

Confidence intervals


Ordinal Omega (total):	[0.87; 0.89]
Ordinal Coefficient Alpha	[0.87; 0.89]

Eigen values

4.234, 1.631, 0.947, 0.603, 0.467, 0.346, 0.318, 0.272 & 0.181

Factor analysis (reproducing only shared variance)

	ML1	ML2
soi_r_attitude_6r	0.574	0.217
soi_r_attitude_4	0.468	0.261
soi_r_attitude_5	0.495	0.366
soi_r_desire_7	-0.028	0.866
soi_r_desire_9	0.054	0.663
soi_r_desire_8	-0.018	0.812
soi_r_behavior_1_discrete	0.482	0.157
soi_r_behavior_2_discrete	0.861	-0.078
soi_r_behavior_3_discrete	0.947	-0.062

Component analysis (reproducing full covariance matrix)

	TC1	TC2
soi_r_attitude_6r	0.752	0.120
soi_r_attitude_4	0.653	0.179
soi_r_attitude_5	0.656	0.306
soi_r_desire_7	-0.001	0.891
soi_r_desire_9	0.030	0.791
soi_r_desire_8	-0.006	0.869
soi_r_behavior_1_discrete	0.590	0.092
soi_r_behavior_2_discrete	0.857	-0.146
soi_r_behavior_3_discrete	0.912	-0.110

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
soi_r_attitude_6r	3.53649893692417	4	1.98501440053078	1.40890539090841	3	0.0375075177962195	1	2	5	5	-0.536260254689111	-1.06465344450765	0.122608079376329	1411	1411
soi_r_attitude_4	3.57760453579022	4	1.88386688179501	1.37254030243014	3	0.0365394157419144	1	2	5	5	-0.539930643050922	-0.99820806842523	0.113394755492558	1411	1411
soi_r_attitude_5	2.90432317505315	3	2.11778980754055	1.45526279672798	2	0.0387416327587885	1	1	4	5	0.0712850730400973	-1.388292057322	0.106661941885188	1411	1411
soi_r_desire_7	2.96456413890858	3	1.5221476645003	1.23375348611475	2	0.0328446687302122	1	2	4	5	0.10597799331091	-1.07355022258838	0.122608079376329	1411	1411
soi_r_desire_9	2.29057406094968	2	1.29706711702882	1.13888854460338	2	0.0303191985993323	1	1	3.5	5	0.686141792861997	-0.379605850598988	0.139262934089298	1411	1411
soi_r_desire_8	2.66761162296244	2	1.17099989444637	1.08212748530216	1	0.0288081202433183	1	1	3	5	0.382946621087799	-0.596469894816504	0.128632175761871	1411	1411
soi_r_behavior_1_discrete	2.34301913536499	2	0.784382084030741	0.885653478529126	1	0.0235776396495983	1	1	3	5	0.923128882744128	0.870286101254663	0.103827072997874	1411	1411
soi_r_behavior_2_discrete	2.43090007087172	2	1.86525727440425	1.36574421997834	2	0.0363584921787354	1	1	4	5	0.483237282976052	-1.02435724789276	0.106661941885188	1411	1411
soi_r_behavior_3_discrete	2.68674698795181	3	2.16563274374092	1.47160889632433	3	0.0391767944278865	1	1	4	5	0.247137127825115	-1.34101387686825	0.0949681077250177	1411	1411

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
soi_r_attitude_6r	Ich möchte nicht eher Sex mit jemandem haben, solange ich mir nicht sicher bin, dass es sich um eine ernste Langzeitbeziehung handelt.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			5	50	0.9669	1	4	5	3.527	1.4051	6	▃▃▁▃▁▆▁▇
soi_r_attitude_4	Ich finde, Sex ohne Liebe ist ok.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			5	50	0.9669	1	4	5	3.565	1.3713	6	▂▃▁▃▁▅▁▇
soi_r_attitude_5	Ich könnte mir vorstellen, dass ich “unverbindlichen” Sex mit verschiedenen Personen genieße und mich dabei wohl fühle.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			5	50	0.9669	1	3	5	2.901	1.4571	6	▇▇▁▅▁▇▁▆
soi_r_desire_7	Wie oft haben Sie Fantasievorstellungen, Sex mit einer Person zu haben, mit der Sie zur Zeit keine feste Beziehung führen?	NA	NA	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	NA	NA	NA	NA	101	0.9332	1	3	5	2.965	1.2338	5	▃▇▁▆▁▆▁▃
soi_r_desire_9	Wie oft haben Sie im Alltag spontan Fantasievorstellungen, Sex mit einer fremden Person zu haben, die Sie irgendwo zufällig gesehen haben?	NA	NA	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	NA	NA	NA	NA	101	0.9332	1	2	5	2.291	1.1389	5	▆▇▁▃▁▃▁▁
soi_r_desire_8	Sociosexual inventory-revised: Desire Subscale	NA	NA	haven_labelled	Niemals, 2. Sehr selten, 3. Etwa einmal im Monat, 4. Etwa einmal die Woche , 5. Fast jeden Tag	NA	NA	NA	NA	101	0.9332	1	2	5	2.668	1.0821	5	▂▇▁▆▁▃▁▁
soi_r_behavior_1_discrete	Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?	NA	NA	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	NA	NA	NA	NA	101	0.9332	1	2	5	2.343	0.8857	5	▂▇▁▃▁▁▁▁
soi_r_behavior_2_discrete	Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?	NA	NA	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	NA	NA	NA	NA	101	0.9332	1	2	5	2.431	1.3657	5	▇▅▁▅▁▃▁▂
soi_r_behavior_3_discrete	Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?	NA	NA	haven_labelled	0, 2. 1, 3. 2-3, 4. 4-7, 5. 8 or more	NA	NA	NA	NA	101	0.9332	1	3	5	2.687	1.4716	5	▇▃▁▅▁▅▁▅

Scale: spms_rel

Overview

Reliability: ω_ordinal [95% CI] = 0.89 [0.88;0.9].

Missing: 570.

Likert plot of scale spms_rel items

Distribution of scale spms_rel

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	spms_self_1, spms_self_2 & spms_self_3R
Observations:	1413
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.85
Omega (hierarchical):	0.04
Revelle’s Omega (total):	0.86
Greatest Lower Bound (GLB):	0.87
Coefficient H:	0.87
Coefficient Alpha:	0.85

Confidence intervals


Omega (total):	[0.84; 0.87]
Coefficient Alpha	[0.84; 0.87]

Estimates assuming ordinal level


Ordinal Omega (total):	0.89
Ordinal Omega (hierarch.):	0.89
Ordinal Coefficient Alpha:	0.89

Confidence intervals


Ordinal Omega (total):	[0.88; 0.9]
Ordinal Coefficient Alpha	[0.88; 0.9]

Eigen values

2.329, 0.4 & 0.271

Factor analysis (reproducing only shared variance)

	ML1
spms_self_1	0.821
spms_self_2	0.881
spms_self_3R	0.746

Component analysis (reproducing full covariance matrix)

	PC1
spms_self_1	0.885
spms_self_2	0.903
spms_self_3R	0.854

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
spms_self_1	3.6135881104034	4	1.06021183305967	1.02966588418752	1	0.0273920945851273	1	3	5	5	-0.604890632650613	-0.0677967009074301	0.128096249115357	1413	1413
spms_self_2	3.4069355980184	3	1.03896036199676	1.01929405080024	1	0.0271161737786514	1	2	4	5	-0.371789608268124	-0.331087106000438	0.159235668789809	1413	1413
spms_self_3R	3.47487615003539	4	1.33453123465032	1.15521912841258	1	0.0307321745024066	1	3	5	5	-0.551497243292905	-0.486209335381379	0.114295824486907	1413	1413

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
spms_self_1	Männer bemerken mich.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	4	5	3.614	1.030	6	▁▂▁▅▁▇▁▃
spms_self_2	Männer fühlen sich zu mir hingezogen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	3	5	3.407	1.019	6	▁▃▁▇▁▇▁▃
spms_self_3R	Ich bekomme von Männern nur selten Komplimente.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	82	99	0.9345	1	4	5	3.475	1.155	6	▂▃▁▅▁▇▁▃

Scale: partner_attractiveness_sexual

Overview

Reliability: ω_ordinal [95% CI] = 0.83 [0.81;0.84].

Missing: 570.

Likert plot of scale partner_attractiveness_sexual items

Distribution of scale partner_attractiveness_sexual

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	partner_sexiness, partner_attractiveness_shortterm, partner_attractiveness_face & partner_attractiveness_body
Observations:	942
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level


Omega (total):	0.74
Omega (hierarchical):	0.12
Revelle’s Omega (total):	0.15
Greatest Lower Bound (GLB):	0.83
Coefficient H:	0.85
Coefficient Alpha:	0.73

Confidence intervals


Omega (total):	[0.71; 0.77]
Coefficient Alpha	[0.7; 0.75]

Estimates assuming ordinal level


Ordinal Omega (total):	0.83
Ordinal Omega (hierarch.):	0.83
Ordinal Coefficient Alpha:	0.81

Confidence intervals


Ordinal Omega (total):	[0.81; 0.84]
Ordinal Coefficient Alpha	[0.79; 0.83]

Eigen values

2.399, 0.802, 0.503 & 0.297

Factor analysis (reproducing only shared variance)

	ML1
partner_sexiness	0.850
partner_attractiveness_shortterm	0.418
partner_attractiveness_face	0.634
partner_attractiveness_body	0.825

Component analysis (reproducing full covariance matrix)

	PC1
partner_sexiness	0.873
partner_attractiveness_shortterm	0.567
partner_attractiveness_face	0.759
partner_attractiveness_body	0.860

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
partner_sexiness	3.91825902335456	4	0.984809718170352	0.992375794832962	2	0.032333350594864	1	3	5	5	-0.757595124942607	0.0698143894960852	0.161889596602972	942	942
partner_attractiveness_shortterm	2.83864118895966	3	1.94205468727085	1.39357622226804	2	0.0454051668832199	1	1	4	5	0.167076555329483	-1.22880570214939	0.111464968152866	942	942
partner_attractiveness_face	4.39384288747346	5	0.613054504513652	0.782977971921083	1	0.0255108008538653	1	4	NA	5	-1.26939323874952	1.45465708755615	0.161889596602972	942	942
partner_attractiveness_body	4.12420382165605	4	0.835779121005571	0.914209560771255	1	0.029786557067899	1	3	5	5	-0.900179528662195	0.213095071108578	0.188428874734607	942	942

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
partner_sexiness	Mein Partner ist sehr sexy.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 82 </td> <td style="text-align:right;"> 570 </td> <td style="text-align:right;"> 0.623 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 3.918 </td> <td style="text-align:right;"> 0.9924 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▂▁▅▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> partner_attractiveness_shortterm </td> <td style="text-align:left;"> Mein Partner ist sehr attraktiv für einen One-Night-Stand oder eine kurze sexuelle Affäre. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		82	570	0.623	1	3	5	2.839	1.3936	7	▇▇▁▇▁▆▁▆
partner_attractiveness_face	Ich finde das Gesicht meines Partners sehr attraktiv.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was not shown to this user., NA. Item was never rendered for this user.	0	s1_demo\(hetero_relationship == 1 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 82 </td> <td style="text-align:right;"> 570 </td> <td style="text-align:right;"> 0.623 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:left;"> 5 </td> <td style="text-align:right;"> 4.394 </td> <td style="text-align:right;"> 0.7830 </td> <td style="text-align:right;"> 7 </td> <td style="text-align:left;"> ▁▁▁▂▁▅▁▇ </td> </tr> <tr> <td style="text-align:left;"> partner_attractiveness_body </td> <td style="text-align:left;"> Ich finde meinen Partner körperlich sehr attraktiv. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 5 agree </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 1. 1: trifft gar nicht zu,<br>2. 2,<br>3. 3,<br>4. 4,<br>5. 5: trifft völlig zu,<br>NA. Item was not shown to this user.,<br>NA. Item was never rendered for this user. </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship == 1		82	570	0.623	1	4	5	4.124	0.9142	7	▁▁▁▃▁▇▁▇

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "s2_initial",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=1512 rows and 191 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "created", "modified", "ended", "expired", "bfi_open_1", "narq_5", "narq_3", "bfi_agree_2", "pvd_infectability_1", "bfi_consc_2r", "soi_r_attitude_6r", "asendorpf_shyness_4r", "bfi_neuro_2r", "bfi_open_2", "bfi_extra_1", "bfi_extra_3", "bfi_agree_3r", "soi_r_attitude_4", "narq_15", "bfi_consc_3", "soi_r_attitude_5", "narq_2", "asendorpf_shyness_2", "bfi_agree_1r", "bfi_consc_1", "narq_11", "bfi_neuro_1", "bfi_extra_2r", "bfi_neuro_3", "narq_18", "bfi_open_3", "asendorpf_shyness_5", "bfi_extra_4", "narq_16", "bfi_agree_4", "bfi_consc_9r", "bfi_neuro_4", "bfi_open_4", "bfi_extra_5r", "bfi_agree_5", "narq_1", "bfi_consc_4r", "bfi_neuro_5r", "bfi_open_5", "bfi_extra_6", "narq_14", "bfi_agree_6r", "bfi_consc_5", "asendorpf_shyness_3r", "pvd_germ_aversion_2", "pvd_germ_aversion_3R", "bfi_neuro_8", "pvd_infectability_3R", "pvd_germ_aversion_1", "feel_safe_walking_dark", "feel_safe_violent_crime", "feel_safe_sexual_assault", "feel_safe_theft", "bfi_open_6", "narq_17", "bfi_extra_7r", "bfi_agree_7", "narq_4", "asendorpf_shyness_1", "bfi_consc_6", "bfi_neuro_6r", "bfi_open_7r", "narq_13", "bfi_extra_8", "bfi_agree_8r", "narq_6", "bfi_consc_7", "bfi_neuro_7", "narq_7", "bfi_open_8", "narq_12", "bfi_open_9r", "bfi_agree_9", "narq_8", "bfi_consc_8r", "narq_9", "narq_10", "bfi_open_10", "pvd_infectability_2", "pvd_germ_aversion_4R", "spms_partner_1", "spms_partner_2", "spms_partner_3R", "satisfaction_sexual_intercourse", "satisfaction_single_life", "investment_potential_partner", "timeperiod_potential_partner", "characteristics_potential_partner", "quantity_potential_partner", "sexual_partner", "fling_frequency", "fling_frequency_2", "relationship_importance", "relationship_importance_partner", "partner_attractiveness_longterm", "partner_attractiveness_shortterm", "partner_attractiveness_face", "partner_attractiveness_body", "attractiveness_warmth", "partner_attractiveness_trust", "net_income_partner", "partner_sexiness", "partner_strength", "partner_feel_safe", "spms_self_1", "spms_self_2", "spms_self_3R", "meet_potential_partner", "partner_height", "meet_potential_partner_other", "partner_weight", "soi_r_behavior_1", "soi_r_behavior_2", "soi_r_behavior_3", "soi_r_desire_9", "soi_r_desire_7", "soi_r_desire_8", "relationship_problems", "relationship_satisfaction_overall", "relationship_conflict", "relationship_satisfaction_2", "relationship_satisfaction_3", "alternatives_1", "alternatives_2", "alternatives_3", "alternatives_4", "alternatives_5", "alternatives_6", "investment_1", "investment_2", "investment_3", "commitment_1", "commitment_2", "commitment_3", "communal_strength_1", "communal_strength_2R", "communal_strength_3", "communal_strength_4", "sexual_communal_strength_1", "sexual_communal_strength_2", "sexual_communal_strength_3", "ecr_avo_1R", "ecr_anx_1", "ecr_avo_2", "ecr_anx_2", "ecr_anx_3", "ecr_avo_3R", "ecr_avo_4", "ecr_anx_4R", "ecr_avo_5R", "ecr_anx_5", "ecr_avo_6", "ecr_anx_6", "free_not_covered", "narq", "bfi_open", "bfi_extra", "bfi_agree", "soi_r_attitude", "bfi_consc", "asendorpf_shyness", "bfi_neuro", "pvd_germ_aversion", "pvd_infectability", "spms_partner", "spms_self", "relationship_satisfaction", "alternatives", "investment", "commitment", "communal_strength", "sexual_communal_strength", "ecr_avo", "ecr_anx", "short", "soi_r_desire", "soi_r_behavior_1_discrete", "soi_r_behavior_2_discrete", "soi_r_behavior_3_discrete", "soi_r_behavior", "soi_r", "spms_rel", "partner_attractiveness_sexual", "relationship_conflict_R", "relationship_problems_R"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_1",
      "description": "Ich sehe mich selbst als jemanden, der originell ist, neue Ideen entwickelt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_5",
      "description": "Ich genieße meine Erfolge sehr.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_3",
      "description": "Ich zeige anderen, was für ein besonderer Mensch ich bin.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_2",
      "description": "Ich sehe mich selbst als jemanden, der hilfsbereit und selbstlos gegenüber anderen ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_infectability_1",
      "description": "Ich bin generell sehr anfällig für Erkältungen, Grippen und andere Infektionen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_2r",
      "description": "Ich sehe mich selbst als jemanden, der etwas achtlos sein kann.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_attitude_6r",
      "description": "Ich möchte nicht eher Sex mit jemandem haben, solange ich mir nicht sicher bin, dass es sich um eine ernste Langzeitbeziehung handelt.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness_4r",
      "description": "Ich finde es leicht, mit Fremden in Kontakt zu kommen.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_2r",
      "description": "Ich sehe mich selbst als jemanden, der entspannt ist, sich durch Stress nicht aus der Ruhe bringen lässt.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_2",
      "description": "Ich sehe mich selbst als jemanden, der vielseitig interessiert ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_1",
      "description": "Ich sehe mich selbst als jemanden, der gesprächig ist, sich gerne unterhält.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_3",
      "description": "Ich sehe mich selbst als jemanden, der voller Energie und Tatendrang ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_3r",
      "description": "Ich sehe mich selbst als jemanden, der häufig in Streitereien verwickelt ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_attitude_4",
      "description": "Ich finde, Sex ohne Liebe ist ok.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_15",
      "description": "Ich ziehe viel Kraft daraus, eine ganz besondere Person zu sein.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_3",
      "description": "Ich sehe mich selbst als jemanden, der zuverlässig ist und gewissenhaft.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_attitude_5",
      "description": "Ich könnte mir vorstellen, dass ich \"unverbindlichen\" Sex mit verschiedenen Personen genieße und mich dabei wohl fühle.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_2",
      "description": "Ich werde einmal berühmt sein.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness_2",
      "description": "Ich fühle mich anderen gegenüber gehemmt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_1r",
      "description": "Ich sehe mich selbst als jemanden, der dazu neigt, andere zu kritisieren.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_1",
      "description": "Ich sehe mich selbst als jemanden, der Aufgaben gründlich erledigt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_11",
      "description": "Ich reagiere häufig gereizt auf Kritik.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_1",
      "description": "Ich sehe mich selbst als jemanden, der deprimiert, niedergeschlagen ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_2r",
      "description": "Ich sehe mich selbst als jemanden, der eher zurückhaltend und reserviert ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_3",
      "description": "Ich sehe mich selbst als jemanden, der leicht angespannt reagiert.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_18",
      "description": "Ich verhalte mich im Umgang mit anderen meist überaus gewandt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_3",
      "description": "Ich sehe mich selbst als jemanden, der tiefsinnig ist, gern über Sachen nachdenkt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness_5",
      "description": "Ich fühle mich auf Parties und in anderen größeren Gruppen unwohl.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_4",
      "description": "Ich sehe mich selbst als jemanden, der begeisterungsfähig ist, andere mitreißen kann.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_16",
      "description": "Mit meinen besonderen Beiträgen schaffe ich es im Mittelpunkt zu stehen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_4",
      "description": "Ich sehe mich selbst als jemanden, der __nicht__ nachtragend ist, anderen leicht vergibt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_9r",
      "description": "Ich sehe mich selbst als jemanden, der dazu neigt, unordentlich zu sein.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_4",
      "description": "Ich sehe mich selbst als jemanden, der sich viele Sorgen macht.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_4",
      "description": "Ich sehe mich selbst als jemanden, der eine lebhafte Vorstellungskraft hat, fantasievoll ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_5r",
      "description": "Ich sehe mich selbst als jemanden, der eher still und wortkarg ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_5",
      "description": "Ich sehe mich selbst als jemanden, der anderen Vertrauen schenkt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_1",
      "description": "Ich bin großartig. ",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_4r",
      "description": "Ich sehe mich selbst als jemanden, der bequem ist und zur Faulheit neigt.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_5r",
      "description": "Ich sehe mich selbst als jemanden, der __nicht__ leicht aus der Fassung zu bringen ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_5",
      "description": "Ich sehe mich selbst als jemanden, der erfinderisch und einfallsreich ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_6",
      "description": "Ich sehe mich selbst als jemanden, der durchsetzungsfähig und energisch ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_14",
      "description": "Andere Menschen sind nichts wert.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_6r",
      "description": "Ich sehe mich selbst als jemanden, der sich kalt und distanziert verhalten kann.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_5",
      "description": "Ich sehe mich selbst als jemanden, der __nicht__ aufgibt, ehe die Aufgabe erledigt ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness_3r",
      "description": "Ich gehe ungezwungen auf andere Menschen zu.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_germ_aversion_2",
      "description": "Ich mag es __nicht__ mit einem Stift zu schreiben, an dem offensichtlich eine andere Person gekaut hat.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_germ_aversion_3R",
      "description": "Es macht mir nichts aus, mit einem Freund eine Wasserflasche zu teilen.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_8",
      "description": "Ich sehe mich selbst als jemanden, der launisch sein kann, schwankende Stimmungen hat.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_infectability_3R",
      "description": "Mein Immunsystem schützt mich vor den meisten Krankheiten, die andere Leute bekommen.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_germ_aversion_1",
      "description": "Am liebsten wasche ich meine Hände direkt, nachdem ich jemandem die Hände geschüttelt habe.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "feel_safe_walking_dark",
      "description": "Ich fühle mich in meiner Gegend sicher, wenn ich alleine in der Dunkelheit unterwegs bin.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "feel_safe_violent_crime",
      "description": "Ich fühle mich in meiner Gegend sicher vor Gewaltverbrechen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "feel_safe_sexual_assault",
      "description": "Ich fühle mich in meiner Gegend sicher vor sexuellen Übergriffen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "feel_safe_theft",
      "description": "Ich fühle mich in meiner Gegend sicher vor Diebstahl.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_6",
      "description": "Ich sehe mich selbst als jemanden, der künstlerische und ästhetische Eindrücke schätzt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_17",
      "description": "Die meisten Menschen sind ziemliche Versager.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_7r",
      "description": "Ich sehe mich selbst als jemanden, der manchmal schüchtern und gehemmt ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_7",
      "description": "Ich sehe mich selbst als jemanden, der rücksichtsvoll und einfühlsam zu anderen ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_4",
      "description": "Ich reagiere genervt, wenn eine andere Person mir die Schau stiehlt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness_1",
      "description": "Ich fühle mich in Gegenwart anderer schüchtern.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_6",
      "description": "Ich sehe mich selbst als jemanden, der tüchtig ist und flott arbeitet.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_6r",
      "description": "Ich sehe mich selbst als jemanden, der ruhig bleibt, selbst in angespannten Situationen ausgeglichen ist.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_7r",
      "description": "Ich sehe mich selbst als jemanden, der routinemäßige und einfache Aufgaben bevorzugt.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_13",
      "description": "Die meisten Menschen werden es zu nichts bringen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra_8",
      "description": "Ich sehe mich selbst als jemanden, der aus sich heraus geht, gesellig ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_8r",
      "description": "Ich sehe mich selbst als jemanden, der schroff und abweisend zu anderen sein kann.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_6",
      "description": "Es freut mich insgeheim, wenn meine Gegner scheitern.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_7",
      "description": "Ich sehe mich selbst als jemanden, der Pläne macht und diese auch durchführt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro_7",
      "description": "Ich sehe mich selbst als jemanden, der leicht nervös und unsicher wird.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_7",
      "description": "In Gesprächen gelingt es mir meist, die Aufmerksamkeit der Anwesenden auf mich zu ziehen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_8",
      "description": "Ich sehe mich selbst als jemanden, der gerne Überlegungen anstellt, mit Ideen spielt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_12",
      "description": "Ich ertrage es nur schlecht, wenn eine andere Person Mittelpunkt des Geschehens ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_9r",
      "description": "Ich sehe mich selbst als jemanden, der nur wenig künstlerisches Interesse hat.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree_9",
      "description": "Ich sehe mich selbst als jemanden, der sich kooperativ verhält, Zusammenarbeit dem Wettbewerb vorzieht.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_8",
      "description": "Ich habe es verdient, als große Persönlichkeit angesehen zu werden.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc_8r",
      "description": "Ich sehe mich selbst als jemanden, der leicht ablenkbar ist, nicht bei der Sache bleibt.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_9",
      "description": "Ich will, dass meine Konkurrenten scheitern.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq_10",
      "description": "Ich genieße es, wenn ein anderer Mensch mir unterlegen ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open_10",
      "description": "Ich sehe mich selbst als jemanden, der sich gut in Musik, Kunst und Literatur auskennt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_infectability_2",
      "description": "Wenn eine Krankheit „gerade umgeht“, bekomme ich sie bestimmt auch.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_germ_aversion_4R",
      "description": "Es macht mir keine Sorgen, von kranken Menschen umgeben zu sein.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_partner_1",
      "description": "Frauen bemerken meinen Partner.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_partner_2",
      "description": "Frauen fühlen sich zu meinem Partner hingezogen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_partner_3R",
      "description": "Mein Partner bekommt von Frauen nur selten Komplimente.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "satisfaction_sexual_intercourse",
      "description": "Der Sex mit meinem Partner ist sehr befriedigend.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "satisfaction_single_life",
      "description": "Ich bin zufrieden mit meinem Singleleben.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "investment_potential_partner",
      "description": "Ich investiere viel, um jemanden kennenzulernen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "timeperiod_potential_partner",
      "description": "Folgende Art von Partnerschaft, suche ich derzeit eher.",
      "value": "no_interest. Ich suche derzeit keine Partnerschaft,\none_night. Kurzfristig (One Night Stand),\nshort. Kurzfristig (Affäre),\nlong. Langfristig (Feste Partnerschaft)",
      "maxValue": "short",
      "minValue": "long",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "characteristics_potential_partner",
      "description": "Ein Partner, der für mich in Frage käme, sollte folgende Eigenschaften haben.",
      "value": "body. körperliche Attraktivität,\nface. attraktives Gesicht,\nmoney. hohes Einkommen,\nsocial_status. hoher sozialer Status,\nintelligence. Intelligenz,\nhumor. Humor,\ncreativity. Kreativität,\ntrustworthiness. Vertrauens- würdigkeit,\npersonality. interessante Persönlich- keit",
      "maxValue": "trustworthiness",
      "minValue": "body",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "quantity_potential_partner",
      "description": "Es befinden sich viele annehmbare Singles in meiner Umgebung.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_partner",
      "description": "Wenn ich sexuell aktiv werde, dann üblicherweise mit Männern...",
      "value": "longterm. mit denen ich mir eine langfristige Beziehung vorstellen kann,\nfriends. mit denen ich befreundet bin,\nmet_before. die ich schon ein paar Mal getroffen habe,\nnew. die ich am gleichen Tag/Abend neu kennen gelernt habe",
      "maxValue": "new",
      "minValue": "friends",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "fling_frequency",
      "description": "Im Monat habe ich durchschnittlich etwa so oft sexuellen Kontakt zu einer anderen Person.",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "fling_frequency_2",
      "description": "Im Monat habe ich durchschnittlich etwa so oft __die Möglichkeit__ zu sexuellen Kontakt zu einer anderen Person.",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_importance",
      "description": "Mir ist die Beziehung zu meinem Partner sehr wichtig.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_importance_partner",
      "description": "Meinem Partner ist die Beziehung zu mir sehr wichtig.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_longterm",
      "description": "Mein Partner ist sehr attraktiv für eine langfristige Beziehung (z.B. als möglicher Ehepartner).",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_shortterm",
      "description": "Mein Partner ist sehr attraktiv für einen One-Night-Stand oder eine kurze sexuelle Affäre.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_face",
      "description": "Ich finde das Gesicht meines Partners sehr attraktiv.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_body",
      "description": "Ich finde meinen Partner körperlich sehr attraktiv.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "attractiveness_warmth",
      "description": "Ich fühle mich bei meinem Partner sehr geborgen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_trust",
      "description": "Das Vertrauen zwischen meinem Partner und mir ist sehr stark.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "net_income_partner",
      "description": "Wie viel Geld hat Ihr Partner monatlich zur Verfügung (netto)?",
      "value": "euro_lt_500.  < 500€,\neuro_500_1000. 500-1000€,\neuro_1000_2000. 1000-2000€,\neuro_2000_3000. 2000-3000€,\neuro_gt_3000. \\> 3000€,\ndont_know. weiß ich nicht,\ndont_tell. möchte ich nicht angeben",
      "maxValue": "euro_lt_500",
      "minValue": "dont_know",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_sexiness",
      "description": "Mein Partner ist sehr sexy.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_strength",
      "description": "Mein Partner ist körperlich stärker als viele andere Männer.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_feel_safe",
      "description": "Mit meinem Partner fühle ich mich sehr sicher.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_self_1",
      "description": "Männer bemerken mich.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_self_2",
      "description": "Männer fühlen sich zu mir hingezogen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spms_self_3R",
      "description": "Ich bekomme von Männern nur selten Komplimente.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "meet_potential_partner",
      "description": "Folgendes tue ich, um einen potentiellen Partner kennen zu lernen.",
      "value": "no_interest. Ich möchte derzeit niemanden kennen lernen,\ndating_app. Dating App,\nonline_dating. Partnerbörse (Internet),\ncontact_ad. Kontaktanzeige,\ngoing_out. Ausgehen (Bars, Clubs, andere Feiern),\nsports. Suche Kontakte im Sportkurs/-verein/ Fitnesstudio,\nsocial_networks. Suche in sozialen Netzwerken,\nfriends. Treffen mit Freunden/ Bekannten / Kollegen,\nother. Andere, und zwar:",
      "maxValue": "sports",
      "minValue": "contact_ad",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_height",
      "description": "Was ist die Körpergröße Ihres Partners in cm (ohne Schuhe)?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "meet_potential_partner_other",
      "description": "Andere:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_weight",
      "description": "Was ist das Gewicht Ihres Partners in kg (ohne Kleidung)?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_1",
      "description": "Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_2",
      "description": "Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_3",
      "description": "Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_desire_9",
      "description": "Wie oft haben Sie im Alltag spontan Fantasievorstellungen, Sex mit einer fremden Person zu haben, die Sie irgendwo zufällig gesehen haben?",
      "value": "1. Niemals,\n2. Sehr selten,\n3. Etwa einmal im Monat,\n4. Etwa einmal die Woche ,\n5. Fast jeden Tag",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_desire_7",
      "description": "Wie oft haben Sie Fantasievorstellungen, Sex mit einer Person zu haben, mit der Sie zur Zeit keine feste Beziehung führen?",
      "value": "1. Niemals,\n2. Sehr selten,\n3. Etwa einmal im Monat,\n4. Etwa einmal die Woche ,\n5. Fast jeden Tag",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_desire_8",
      "description": "Sociosexual inventory-revised: Desire Subscale",
      "value": "1. Niemals,\n2. Sehr selten,\n3. Etwa einmal im Monat,\n4. Etwa einmal die Woche ,\n5. Fast jeden Tag",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "relationship_problems",
      "description": "Es gibt viele Probleme in meiner Beziehung.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_satisfaction_overall",
      "description": "Ich bin im Großen und Ganzen zufrieden mit meiner Beziehung.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_conflict",
      "description": "Es gibt oft Streit/Meinungsverschiedenheiten in meiner Partnerschaft.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_satisfaction_2",
      "description": "In unserer Beziehung werden meine Bedürfnisse (z.B. nach Intimität, Gemeinsamkeit, etc.) erfüllt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_satisfaction_3",
      "description": "Unsere Beziehung macht mich sehr glücklich.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_1",
      "description": "Ich finde auch andere Personen als meinen Partner, mit denen ich eine Beziehung haben könnte, sehr anziehend.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_2",
      "description": "Die Alternativen zu unserer Beziehung (z.B. andere Partnerschaft, mit Freunden zusammen sein, allein sein) sind für mich sehr reizvoll.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_3",
      "description": "Ich flirte mit Männern, ohne dass diese wissen, dass ich in einer Partnerschaft bin.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_4",
      "description": "Meine Bedürfnisse (z.B. nach Intimität, Gemeinsamkeit, etc.) könnten mit Leichtigkeit in einer anderen Beziehung erfüllt werden.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_5",
      "description": "Mir ist sehr bewusst, dass es \"da draußen\" noch viele andere attraktive potentielle Partner für mich gibt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives_6",
      "description": "Es wäre leicht für mich, einen Partner für eine neue Beziehung zu finden.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "investment_1",
      "description": "Ich habe viel in unsere Beziehung hineingesteckt, das ich verlieren würde, wenn die Beziehung zu Ende wäre.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "investment_2",
      "description": "Viele Aspekte meines Lebens sind so eng mit meinem Partner verbunden (z.B. Freizeitgestaltung, gemeinsamer Freundes- und Bekanntenkreis), dass ich all dies verlieren würde, wenn wir uns trennen würden.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "investment_3",
      "description": "Ich investiere viel (z.B. Zeit, kleine Aufmerksamkeiten, Geschenke) in die Beziehung zu meinem Partner.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "commitment_1",
      "description": "Ich möchte, dass unsere Beziehung noch sehr lange dauert.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "commitment_2",
      "description": "Ich orientiere mich an einer langfristigen Zukunft unserer Partnerschaft (z.B. stelle mit unser Zusammensein in einigen Jahren vor, mache Pläne für die Zukunft).",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "commitment_3",
      "description": "Es würde mich sehr aus der Fassung bringen, wenn unsere Beziehung in nächster Zeit enden würde.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "communal_strength_1",
      "description": "Die Bedürfnisse meines Partners zu erfüllen hat für mich hohe Priorität.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "communal_strength_2R",
      "description": "Für meinen Partner Opfer zu bringen widerstrebt mir.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "communal_strength_3",
      "description": "Ich würde keine Mühen scheuen um etwas für meinen Partner zu tun.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "communal_strength_4",
      "description": "Wenn es meinem Partner einmal nicht gut geht, bin ich für ihn da, auch wenn ich dafür eigene Bedürfnisse hinten anstellen muss.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_communal_strength_1",
      "description": "Ich gebe mir große Mühe, um die sexuellen Bedürfnisse meines Partners zu erfüllen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_communal_strength_2",
      "description": "Die sexuellen Bedürfnisse meines Partners zu erfüllen hat für mich hohe Priorität.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_communal_strength_3",
      "description": "Um die sexuellen Bedürfnisse meines Partners zu erfüllen, bin ich bereit, meine eigenen sexuellen Bedürfnisse hintenan zu stellen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_1R",
      "description": "Es hilft mir, mich an meinen Partner zu wenden, wenn ich es brauche.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_1",
      "description": "Ich brauche die Bestätigung, dass mein Partner mich liebt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_2",
      "description": "Ich möchte meinem Partner nahe sein, halte mich aber trotzdem zurück.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_2",
      "description": "Mein Verlangen nach Nähe schreckt meinen Partner manchmal ab.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_3",
      "description": "Ich finde, mein Partner will __nicht__ so viel Nähe wie ich.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_3R",
      "description": "Ich wende mich oft an meinen Partner, z. B. wenn ich Trost oder Bestätigung brauche.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_4",
      "description": "Ich versuche zu vermeiden, meinem Partner zu nahe zu kommen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_4R",
      "description": "Ich mache mir kaum Gedanken darüber, dass ich verlassen werden könnte.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_5R",
      "description": "Ich bespreche meine Sorgen und Probleme meistens mit meinem Partner.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_5",
      "description": "Es frustriert mich, wenn ich gerne meinen Partner bei mir hätte und er nicht da ist.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo_6",
      "description": "Ich werde nervös, wenn mein Partner mir zu nahe kommt.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx_6",
      "description": "Ich mache mir Gedanken darüber, dass  mein Partner sich nicht so um mich kümmert wie ich mich um ihn.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "free_not_covered",
      "description": "Falls Fragen für Sie nicht oder nur falsch beantwortbar waren, oder Sie ansonsten den Eindruck haben, dass uns hier etwas wichtiges entging, geben Sie es bitte in diesem offenen Feld an.\n<small>optional<\/small>",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "narq",
      "description": "18 narq items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_open",
      "description": "10 bfi_open items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_extra",
      "description": "8 bfi_extra items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_agree",
      "description": "9 bfi_agree items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_attitude",
      "description": "3 soi_r_attitude items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_consc",
      "description": "9 bfi_consc items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "asendorpf_shyness",
      "description": "5 asendorpf_shyness items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "bfi_neuro",
      "description": "8 bfi_neuro items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_germ_aversion",
      "description": "4 pvd_germ_aversion items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "pvd_infectability",
      "description": "3 pvd_infectability items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "spms_partner",
      "description": "3 spms_partner items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "spms_self",
      "description": "3 spms_self items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_satisfaction",
      "description": "Relationship satisfaction",
      "@type": "propertyValue"
    },
    {
      "name": "alternatives",
      "description": "6 alternatives items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "investment",
      "description": "3 investment items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "commitment",
      "description": "3 commitment items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "communal_strength",
      "description": "4 communal_strength items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_communal_strength",
      "description": "3 sexual_communal_strength items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_avo",
      "description": "6 ecr_avo items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "ecr_anx",
      "description": "6 ecr_anx items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_desire",
      "description": "3 soi_r_desire items aggregated by robust_rowmeans",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_1_discrete",
      "description": "Mit wie vielen verschiedenen Personen haben Sie in den letzten 12 Monaten Geschlechtsverkehr gehabt?",
      "value": "1. 0,\n2. 1,\n3. 2-3,\n4. 4-7,\n5. 8 or more",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_2_discrete",
      "description": "Mit wie vielen verschiedenen Personen haben Sie in Ihrem Leben nur einmal Geschlechtsverkehr gehabt?",
      "value": "1. 0,\n2. 1,\n3. 2-3,\n4. 4-7,\n5. 8 or more",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior_3_discrete",
      "description": "Mit wie vielen verschiedenen Personen hatten Sie schon Geschlechtsverkehr, ohne dabei ein Interesse an einer längerfristigen Beziehung mit dieser Person zu haben?",
      "value": "1. 0,\n2. 1,\n3. 2-3,\n4. 4-7,\n5. 8 or more",
      "maxValue": 5,
      "minValue": 1,
      "@type": "propertyValue"
    },
    {
      "name": "soi_r_behavior",
      "description": "Sociosexual inventory-revised: Behaviour Subscale",
      "@type": "propertyValue"
    },
    {
      "name": "soi_r",
      "description": "Sociosexual inventory-revised",
      "@type": "propertyValue"
    },
    {
      "name": "spms_rel",
      "description": "3 spms_self items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "partner_attractiveness_sexual",
      "description": "Partner's sexual attractiveness",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_conflict_R",
      "description": "Es gibt oft Streit/Meinungsverschiedenheiten in meiner Partnerschaft.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_problems_R",
      "description": "Es gibt viele Probleme in meiner Beziehung.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    }
  ]
}`

Diary

Participants received invitations to fill out the diary daily over a period of 70 days.

Metadata

Description

Dataset name: Goettigen Ovulatory Cycle Diaries 2

A 70-day online diary study focusing on menstrual cycles, sexuality, mood, and behaviour

Metadata for search engines

Temporal Coverage: 2014-2015
Spatial Coverage: German-speaking countries, online
Citation: Arslan, R.C., Driebe, XXXX
URL: https://rubenarslan.github.io/gocd2
Identifier: https://doi.org/10.17605/OSF.IO/XXXX
Date published: 2020-06-02
Creator:

name

value

1

Ruben C. Arslan

x
session
short
created_date
created
modified
ended
expired
browser
andere
andere_uc
anderen
anderer
days_done
days_since_beginning
days_since_last_entry
never_skipped_more_than_2
money_earned
refer_time_period
good_mood
self_esteem
relationship_satisfaction
stressed
irritable
loneliness
risk_taking
illness_pain
illness_pain_specific
illness_pain_other
partner_illness_pain
partner_illness_pain_specific
partner_illness_pain_other
following_usual_routine
everyday_specify
travel
travel_how
sleep_amount
sleep_quality
sleep_fell_asleep_time
sleep_awoke_time
time_friends
time_work_uni
time_sports
time_people
time_family
food_amount
meat
alcohol
smoking
grooming_1
grooming_2
grooming_time_spent
vanity_1
vanity_2
vanity_3
grooming_activities
skin
hair
social_life_active
social_life_saw_people
social_life_thought_about
social_life_free
relationship_change
relationship_change_specify
night_spent_with_partner
contact_partner
saw_partner_last
love_showed_to_partner
love_shown_by_partner
mate_retention1
mate_retention2
mate_retention3
conflict_partner
desirability
high_libido
is_single
sexual_desire_for_whom
sexual_initiation_self
sexual_initiation_partner
in_pair_desire_1
in_pair_desire_2R
in_pair_desire_3R
in_pair_desire_4
in_pair_went_out
in_pair_desire_6
in_pair_desire_7
in_pair_desire_8
in_pair_desire_9
in_pair_desire_10
in_pair_desire_11
in_pair_desire_12
in_pair_desire_13
in_pair_desire_14
in_pair_desire_5R
extra_pair_desire_1
extra_pair_desire_2R
extra_pair_desire_3R
extra_pair_desire_4
extra_pair_went_out
extra_pair_desire_6
extra_pair_desire_7
extra_pair_desire_8
extra_pair_desire_9
extra_pair_desire_10
extra_pair_desire_11
extra_pair_desire_12
extra_pair_desire_13
extra_pair_desire_14
extra_pair_desire_5R
extra_pair_desire_16
sexual_desire_wants_desire
sexual_desire_fulfill_sex_needs
sexual_desire_fulfill_partner
sexual_desire_for_activity
last_had_sex
sex_active
no_sex_reason
sex_acts
sex_1_time
sex_1_withwhom
sex_1_activity
sex_1_contraception
sex_1_happy
sex_1_enjoyed
sex_1_partner_enjoyed
sex_1_fantasy_partner
sex_1_fantasy_actions
sex_2_time
sex_2_withwhom
sex_2_activity
sex_2_contraception
sex_2_happy
sex_2_enjoyed
sex_2_partner_enjoyed
sex_2_fantasy_partner
sex_2_fantasy_actions
menstrual_pain
special_events_love_life
menstruation_since_last_entry
menstruation_today
menstrual_onset
menstrual_onset_date
spotting
answered_honestly_today
dishonest_answers
notes_to_us
grooming
vanity
mate_retention
in_pair_desire
extra_pair_desire
weekday
weekend
sleep_duration
first_diary_day
progesterone_mean
progesterone_diff
progesterone_log_mean
progesterone_log_diff
estradiol_mean
estradiol_diff
estradiol_log_mean
estradiol_log_diff
ibl_estradiol_mean
ibl_estradiol_diff
ibl_estradiol_log_mean
ibl_estradiol_log_diff
testosterone_mean
testosterone_diff
testosterone_log_mean
testosterone_log_diff
cortisol_mean
cortisol_diff
cortisol_log_mean
cortisol_log_diff
window_length
date_of_ovulation_awareness
diary_day_observation
next_menstrual_onset
last_menstrual_onset
menstrual_onset_days_until
menstrual_onset_days_since
date_origin
menstruation_labelled
next_menstrual_onset_if_no_last
day_number
number_of_cycles
cycle_nr
cycle_length
cycle_nr_fully_observed
mean_cycle_length_diary
median_cycle_length_diary
next_menstrual_onset_inferred
RCD_inferred
luteal_BC
follicular_FC
day_lh_surge
day_of_ovulation
day_of_ovulation_inferred
day_of_ovulation_forward_counted
date_of_ovulation_BC
date_of_ovulation_inferred
date_of_ovulation_forward_counted
date_of_ovulation_LH
DRLH
date_of_ovulation_awareness_nr
fertile_awareness
date_of_ovulation_avg_follicular
date_of_ovulation_avg_luteal
date_of_ovulation_avg_luteal_inferred
FCD
RCD
DAL
RCD_squished
RCD_squished_rounded
RCD_inferred_squished
RCD_rel_to_ovulation
RCD_fab
conception_risk_lh
fertile_lh
prc_stirn_b
prc_wcx_b
fertile_narrow
fertile_broad
fertile_window
premenstrual_phase
prc_stirn_b_squished
prc_wcx_b_squished
fertile_narrow_squished
fertile_broad_squished
fertile_window_squished
premenstrual_phase_squished
prc_stirn_b_inferred_squished
prc_wcx_b_inferred_squished
fertile_narrow_inferred_squished
fertile_broad_inferred_squished
fertile_window_inferred_squished
premenstrual_phase_inferred_squished
prc_stirn_b_forward_counted
prc_wcx_b_forward_counted
fertile_narrow_forward_counted
fertile_broad_forward_counted
fertile_window_forward_counted
premenstrual_phase_forward_counted
prc_stirn_b_aware_luteal
prc_wcx_b_aware_luteal
fertile_narrow_aware_luteal
fertile_broad_aware_luteal
fertile_window_aware_luteal
premenstrual_phase_aware_luteal
prc_stirn_b_inferred
prc_wcx_b_inferred
fertile_narrow_inferred
fertile_broad_inferred
fertile_window_inferred
premenstrual_phase_inferred
fertile_fab
premenstrual_phase_fab
menstruation_imputed
menstruation
extra_pair_desire_and_behaviour
extra_pair_interest
in_pair_desire_and_behaviour
in_pair_interest
grooming_broad
saw_partner
last_saw_partner_date
days_since_seeing_partner
time_since_seeing_partner

Survey overview

61187 completed rows, 62043 who entered any information, 623 only viewed the first page. There are 1470 expired rows (people who did not finish filling out in the requested time frame). In total, there are 62666 rows including unfinished and expired rows.

There were 1373 unique participants, of which 1345 finished filling out at least one survey.

This survey was repeated many times, on average 45.64 times per user.

Number of sessions

The first session started on 2016-05-03 17:10:11, the last session on 2017-03-23 21:45:40.

Starting date times

People took on average 11.8 minutes (median 4) to answer the survey.

Duration people took for answering the survey

#Variables

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	1373	0	7	7	0	NA

created_date

Distribution

## 325  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
created_date	Date	0	1	325	2016-05-03	2016-10-11	2017-03-23	NA

browser

Distribution

Distribution of values for browser

1 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
browser		server	HTTP_USER_AGENT	character	1			1	1	1	1612	0	61	216	0

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
server	HTTP_USER_AGENT	browser		1			1

Value labels

Response choices
name	value

andere

Distribution

Distribution of values for andere

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
andere		calculate	character	0		ifelse(s1_demo$hetero_relationship, ‘andere’, ’ ’)	2	2	1	2	0	1	6	21120

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	andere		0		ifelse(s1_demo$hetero_relationship, ‘andere’, ’ ’)	2

Value labels

Response choices
name	value

andere_uc

Distribution

Distribution of values for andere_uc

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
andere_uc		calculate	character	0		ifelse(s1_demo$hetero_relationship, ‘Andere’, ’ ’)	3	2	1	2	0	1	6	21120

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	andere_uc		0		ifelse(s1_demo$hetero_relationship, ‘Andere’, ’ ’)	3

Value labels

Response choices
name	value

anderen

Distribution

Distribution of values for anderen

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
anderen		calculate	character	0		ifelse(s1_demo$hetero_relationship, ‘anderen’, ’ ’)	4	2	1	2	0	1	7	21120

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	anderen		0		ifelse(s1_demo$hetero_relationship, ‘anderen’, ’ ’)	4

Value labels

Response choices
name	value

anderer

Distribution

Distribution of values for anderer

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
anderer		calculate	character	0		ifelse(s1_demo$hetero_relationship, ‘anderer’, ’ ’)	5	2	1	2	0	1	7	21120

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	anderer		0		ifelse(s1_demo$hetero_relationship, ‘anderer’, ’ ’)	5

Value labels

Response choices
name	value

days_done

Distribution

Distribution of values for days_done

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
days_done		calculate	character	0		sum(!is.na(s3_daily$ended))	6	2	1	71	0	1	2	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	days_done		0		sum(!is.na(s3_daily$ended))	6

Value labels

Response choices
name	value

days_since_beginning

Distribution

Distribution of values for days_since_beginning

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
days_since_beginning		calculate	character	0		library(lubridate) as.numeric(Sys.Date() - as.Date( s1_demo$created ), units = ‘days’)	7	2	1	80	0	1	3	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	days_since_beginning		0		library(lubridate) as.numeric(Sys.Date() - as.Date( s1_demo$created ), units = ‘days’)	7

Value labels

Response choices
name	value

days_since_last_entry

Distribution

Distribution of values for days_since_last_entry

1411 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
days_since_last_entry		calculate	character	0		if(days_done > 0) { library(lubridate) round(as.numeric(now() - as.POSIXct( last(s3_daily$ended) ), units = ‘days’)) } else { NA }	8	1411	0.9775	38	0	1	2	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	days_since_last_entry		0		if(days_done > 0) { library(lubridate) round(as.numeric(now() - as.POSIXct( last(s3_daily$ended) ), units = ‘days’)) } else { NA }	8

Value labels

Response choices
name	value

never_skipped_more_than_2

Distribution

Distribution of values for never_skipped_more_than_2

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
never_skipped_more_than_2		calculate	character	0		ifelsena(sum(floor(as.numeric(diff(as.POSIXct(na.omit(s3_daily$ended))), units = ‘days’)) > 2) > 1, 0, 1)	9	2	1	2	0	1	1	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	never_skipped_more_than_2		0		ifelsena(sum(floor(as.numeric(diff(as.POSIXct(na.omit(s3_daily$ended))), units = ‘days’)) > 2) > 1, 0, 1)	9

Value labels

Response choices
name	value

money_earned

Distribution

Distribution of values for money_earned

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
money_earned		calculate	character	0		5 + days_done * 0.5 + 0.5 + ifelse(never_skipped_more_than_2, 5, 0)	10	2	1	80	0	1	4	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	money_earned		0		5 + days_done * 0.5 + 0.5 + ifelse(never_skipped_more_than_2, 5, 0)	10

Value labels

Response choices
name	value

refer_time_period

Distribution

Distribution of values for refer_time_period

2 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
refer_time_period		calculate	character	0		if(is.na(days_since_last_entry) \| days_since_last_entry > 1) { “in den letzten 24 Stunden” } else { “seit meinem letzten Eintrag” }	11	2	1	2	0	25	27	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	refer_time_period		0		if(is.na(days_since_last_entry) \| days_since_last_entry > 1) { “in den letzten 24 Stunden” } else { “seit meinem letzten Eintrag” }	11

Value labels

Response choices
name	value

good_mood

Meine Stimmung war gut.

Distribution

Distribution of values for good_mood

13170 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	good_mood	Meine Stimmung war gut.	0	rating_button_label_width150 blank_button	runif(1) < 0.8		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

self_esteem

Ich war zufrieden mit mir.

Distribution

Distribution of values for self_esteem

13171 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	self_esteem	Ich war zufrieden mit mir.	0	rating_button_label_width150 blank_button	runif(1) < 0.8		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

relationship_satisfaction

Ich war zufrieden mit meiner Beziehung.

Distribution

Distribution of values for relationship_satisfaction

29815 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	relationship_satisfaction	Ich war zufrieden mit meiner Beziehung.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.8		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

stressed

Ich war gestresst.

Distribution

Distribution of values for stressed

37916 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	stressed	Ich war gestresst.	0	rating_button_label_width150 blank_button	runif(1) < 0.4		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

irritable

Ich war leicht reizbar.

Distribution

Distribution of values for irritable

37800 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	irritable	Ich war leicht reizbar.	0	rating_button_label_width150 blank_button	runif(1) < 0.4		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

loneliness

Ich war einsam.

Distribution

Distribution of values for loneliness

37973 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	loneliness	Ich war einsam.	0	rating_button_label_width150 blank_button	runif(1) < 0.4		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

risk_taking

Ich war risikobereit.

Distribution

Distribution of values for risk_taking

50337 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	risk_taking	Ich war risikobereit.	0	rating_button_label_width150 blank_button	runif(1) < 0.2		22

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

illness_pain

Ich war krank/hatte Schmerzen.

Distribution

Distribution of values for illness_pain

844 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	illness_pain	Ich war krank/hatte Schmerzen.	0	rating_button_label_width150 blank_button			23

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

illness_pain_specific

Das hatte ich: (Mehrfachnennungen möglich)

Distribution

Distribution of values for illness_pain_specific

40857 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		illness_pain_specific	Das hatte ich: <small>(Mehrfachnennungen möglich)</small>	1	mc_vertical	illness_pain > 0		24

Value labels

Response choices
name	value
1	headache
2	migraine
3	bladder_infection
4	cold
5	flu
6	gastrointestinal
7	back_pain
8	other

illness_pain_other

andere:

Distribution

Distribution of values for illness_pain_other

54868 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
illness_pain_other	andere:	text	character	0	illness_pain_specific %contains%“other”		25	54868	0.1244	2316	0	1	221	9

Item

Item options
type	name	label	optional	showif	value	item_order
text	illness_pain_other	andere:	0	illness_pain_specific %contains%“other”		25

Value labels

Response choices
name	value

partner_illness_pain

Mein Partner war krank/hatte Schmerzen.

Distribution

Distribution of values for partner_illness_pain

21658 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	partner_illness_pain	Mein Partner war krank/hatte Schmerzen.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship		26

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

partner_illness_pain_specific

Das hatte er: (Mehrfachnennungen möglich)

Distribution

Distribution of values for partner_illness_pain_specific

56214 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		partner_illness_pain_specific	Das hatte er: <small>(Mehrfachnennungen möglich)</small>	1	mc_vertical	partner_illness_pain > 0		27

Value labels

Response choices
name	value
1	headache
2	migraine
3	bladder_infection
4	cold
5	flu
6	gastrointestinal
7	back_pain
8	other

partner_illness_pain_other

andere:

Distribution

Distribution of values for partner_illness_pain_other

60881 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
partner_illness_pain_other	andere:	text	character	0	partner_illness_pain_specific %contains% “other”		28	60881	0.0285	580	0	1	113	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	partner_illness_pain_other	andere:	0	partner_illness_pain_specific %contains% “other”		28

Value labels

Response choices
name	value

following_usual_routine

Ich bin meinem Alltag nachgegangen.

Distribution

Distribution of values for following_usual_routine

1064 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		following_usual_routine	Ich bin meinem Alltag nachgegangen.	0	right100 left500			31

Value labels

Response choices
name	value
Nein	0
Ja	1

everyday_specify

Das war anders als sonst:

Distribution

Distribution of values for everyday_specify

49604 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
everyday_specify	Das war anders als sonst:	textarea	character	0	following_usual_routine == 0		32	49604	0.2084	7801	0	1	740	11

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	everyday_specify	Das war anders als sonst:	0	following_usual_routine == 0		32

Value labels

Response choices
name	value

travel

Ich bin gereist.

Distribution

Distribution of values for travel

49604 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		travel	Ich bin gereist.	0	right100 left500	following_usual_routine == 0		33

Value labels

Response choices
name	value
Nein	0
Ja	1

travel_how

So sah meine Reise aus: (Mehrfachnennungen möglich)

Distribution

Distribution of values for travel_how

57881 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		travel_how	So sah meine Reise aus: <small>(Mehrfachnennungen möglich)</small>	0	square square80	travel == 1		34

Value labels

Response choices
name	value
1	alone
2	with_family
3	with_friends
4	with_partner
5	job_related
6	vacation
7	visit
8	old_home

sleep_amount

So viel habe ich letzte Nacht geschlafen:

Distribution

Distribution of values for sleep_amount

31897 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	sleep_amount	So viel habe ich letzte Nacht geschlafen:	0	rating_button_label_width150 blank_button	runif(1) < 0.5		35

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

sleep_quality

Mein Schlaf letzte Nacht war gut.

Distribution

Distribution of values for sleep_quality

31945 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sleep_quality	Mein Schlaf letzte Nacht war gut.	0	rating_button_label_width150 blank_button	runif(1) < 0.5		35

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

sleep_fell_asleep_time

Distribution

Distribution of values for sleep_fell_asleep_time

31917 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
sleep_fell_asleep_time	numeric	31917	0.4907	0	10800	86340	36012	37866	▇▁▁▁▆	NA

sleep_awoke_time

Distribution

Distribution of values for sleep_awoke_time

31917 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
sleep_awoke_time	numeric	31917	0.4907	0	28800	86340	30027	7078	▁▇▂▁▁	NA

time_friends

Ich habe Zeit mit Freunden verbracht.

Distribution

Distribution of values for time_friends

19369 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	time_friends	Ich habe Zeit mit Freunden verbracht.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		38

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

time_work_uni

Ich habe Zeit mit Arbeiten/Uni verbracht.

Distribution

Distribution of values for time_work_uni

19711 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	time_work_uni	Ich habe Zeit mit Arbeiten/Uni verbracht.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		38

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

time_sports

Ich habe Sport getrieben.

Distribution

Distribution of values for time_sports

19649 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	time_sports	Ich habe Sport getrieben.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		38

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

time_people

Ich haben Kontakt zu anderen Menschen gesucht.

Distribution

Distribution of values for time_people

19450 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	time_people	Ich haben Kontakt zu anderen Menschen gesucht.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		38

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

time_family

Ich habe Kontakt zu meiner Familie gesucht.

Distribution

Distribution of values for time_family

19540 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	time_family	Ich habe Kontakt zu meiner Familie gesucht.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		38

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

food_amount

So viel habe ich gegessen:

Distribution

Distribution of values for food_amount

19561 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	food_amount	So viel habe ich gegessen:	0	rating_button_label_width150 blank_button	runif(1) < 0.7		39

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

meat

Ich habe Fleisch gegessen.

Distribution

Distribution of values for meat

29933 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	meat	Ich habe Fleisch gegessen.	0	rating_button_label_width150 blank_button	! s1_demo$meat_eating %contains% “veg” & runif(1) < 0.7		39

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

alcohol

Ich habe Alkohol getrunken.

Distribution

Distribution of values for alcohol

19466 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	alcohol	Ich habe Alkohol getrunken.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		39

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

smoking

Ich habe geraucht.

Distribution

Distribution of values for smoking

19705 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	smoking	Ich habe geraucht.	0	rating_button_label_width150 blank_button	runif(1) < 0.7		39

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

grooming_time_spent

So viele Minuten habe ich insgesamt investiert, um mich ausgehfertig zu machen:

Distribution

Distribution of values for grooming_time_spent

44111 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	min	median	max	mean	sd	hist
grooming_time_spent	So viele Minuten habe ich insgesamt investiert, um mich ausgehfertig zu machen:	number	0,240	numeric	0	runif(1) < 0.3		42	right100 left500	44111	0.2961	0	15	240	18.49	16.96	▇▁▁▁▁

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
number	0,240	grooming_time_spent	So viele Minuten habe ich insgesamt investiert, um mich ausgehfertig zu machen:	0	right100 left500	runif(1) < 0.3		42

Value labels

Response choices
name	value

grooming_activities

Heute hab ich mir die … (Mehrfachnennungen möglich)

Distribution

Distribution of values for grooming_activities

44314 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		grooming_activities	Heute hab ich mir die … <small>(Mehrfachnennungen möglich)</small>	1	square square80	runif(1) < 0.3		42

Value labels

Response choices
name	value
1	shaved_legs
2	shaved_armpits
3	shaved_bikini_zone
4	plucked_eyebrows
5	made_hair

skin

Meine Haut war… (Mehrfachnennungen möglich)

Distribution

Distribution of values for skin

44121 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		skin	Meine Haut war… <small>(Mehrfachnennungen möglich)</small>	0	square square80	runif(1) < 0.3		42

Value labels

Response choices
name	value
1	super
2	as_always
3	fattier
4	drier
5	more_pimples
6	wrinklier
7	more_sensitive

hair

Meine Haare waren… (Mehrfachnennungen möglich)

Distribution

Distribution of values for hair

44253 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		hair	Meine Haare waren… <small>(Mehrfachnennungen möglich)</small>	0	square square80	runif(1) < 0.3		42

Value labels

Response choices
name	value
1	super
2	as_always
3	fattier
4	drier
5	freshly_washed
6	freshly_coloured
7	untameable

social_life_active

Ich war sozial aktiv.

Distribution

Distribution of values for social_life_active

41939 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		social_life_active	Ich war sozial aktiv.	0	mc_vertical	! s1_demo$hetero_relationship		53

Value labels

Response choices
name	value
1	was_alone
2	barely
3	job_uni_related
4	met_one_purposefully
5	met_several_purposefully

social_life_saw_people

Mit diesen Menschen hatte ich längeren sozialen Kontakt (mehr als eine Stunde).

Distribution

Distribution of values for social_life_saw_people

46874 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_multiple	social_life_saw_people	Mit diesen Menschen hatte ich längeren sozialen Kontakt (mehr als eine Stunde).	1	! s1_demo$hetero_relationship		54

Value labels

Response choices
name	value
1	1

social_life_thought_about

An diese Menschen habe ich viel gedacht und hätte sie gerne gesehen.

Distribution

Distribution of values for social_life_thought_about

53258 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	showif	value	item_order
select_or_add_multiple	social_life_thought_about	An diese Menschen habe ich viel gedacht und hätte sie gerne gesehen.	1	! s1_demo$hetero_relationship		55

Value labels

Response choices
name	value
1	1

social_life_free

Das habe ich sozial unternommen: optional

Distribution

Distribution of values for social_life_free

56399 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
social_life_free	Das habe ich sozial unternommen: <small>optional</small>	textarea	character	1	! s1_demo$hetero_relationship		56	56399	0.1	5371	0	1	1682	9

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	social_life_free	Das habe ich sozial unternommen: <small>optional</small>	1	! s1_demo$hetero_relationship		56

Value labels

Response choices
name	value

relationship_change

In meiner Beziehung hat sich etwas Wichtiges verändert: (Mehrfachnennungen möglich)

Distribution

Distribution of values for relationship_change

21862 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc_multiple	relationship_change	In meiner Beziehung hat sich etwas Wichtiges verändert: <small>(Mehrfachnennungen möglich)</small>	0	mc_vertical	s1_demo$hetero_relationship		59

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4
5	5

relationship_change_specify

Folgendes möchte ich dazu noch sagen:

Distribution

Distribution of values for relationship_change_specify

61815 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
relationship_change_specify	Folgendes möchte ich dazu noch sagen:	textarea	character	1	relationship_change != 1 & relationship_change != ""		60	61815	0.0136	750	0	1	725	2

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	relationship_change_specify	Folgendes möchte ich dazu noch sagen:	1	relationship_change != 1 & relationship_change != ""		60

Value labels

Response choices
name	value

night_spent_with_partner

Ich habe die letzte Nacht mit meinem Partner verbracht.

Distribution

Distribution of values for night_spent_with_partner

21862 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		night_spent_with_partner	Ich habe die letzte Nacht mit meinem Partner verbracht.	0	right100 left500	s1_demo$hetero_relationship		61

Value labels

Response choices
name	value
Nein	0
Ja	1

contact_partner

Ich habe r refer_time_period…

Distribution

Distribution of values for contact_partner

21862 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc	contact_partner	Ich habe `r refer_time_period`…	0	mc_vertical	s1_demo$hetero_relationship		62

Value labels

Response choices
name	value
…fast die ganze Zeit mit meinem Partner verbracht.	1
…viel Zeit mit meinem Partner verbracht.	2
…mehrere Stunden mit meinem Partner verbracht.	3
…meinen Partner nur kurz gesehen.	4
…meinen Partner nicht gesehen, aber mehrfach mit ihm kommuniziert.	5
…meinen Partner nicht gesehen, aber einmal mit ihm kommuniziert.	6
…meinen Partner weder gesehen, noch mit ihm kommuniziert.	7

saw_partner_last

Ich habe meinen Partner vor heute zuletzt gesehen:

Distribution

Distribution of values for saw_partner_last

57182 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		saw_partner_last	Ich habe meinen Partner vor heute zuletzt gesehen:	0	mc_vertical	s1_demo$hetero_relationship & days_since_last_entry > 1		63

Value labels

Response choices
name	value
gestern	1
vorgestern	2
vor drei Tagen	3
vor 4 Tagen	4
vor 5 Tagen	5
vor 6 Tagen	6
vor ein bis zwei Wochen	7
vor mehr als zwei Wochen	8

love_showed_to_partner

Ich habe meinem Partner gezeigt, dass ich ihn liebe.

Distribution

Distribution of values for love_showed_to_partner

50438 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	love_showed_to_partner	Ich habe meinem Partner gezeigt, dass ich ihn liebe.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.3		64

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

love_shown_by_partner

Mein Partner hat mir gezeigt, dass er mich liebt.

Distribution

Distribution of values for love_shown_by_partner

50478 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	love_shown_by_partner	Mein Partner hat mir gezeigt, dass er mich liebt.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.3		64

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

conflict_partner

Ich hatte Streit mit meinem Partner.

Distribution

Distribution of values for conflict_partner

50406 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	conflict_partner	Ich hatte Streit mit meinem Partner.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.3		64

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

desirability

Ich habe mich sexuell begehrenswert gefühlt.

Distribution

Distribution of values for desirability

42294 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 less_to_more	desirability	Ich habe mich sexuell begehrenswert gefühlt.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.5		71

Value labels

Response choices
name	value
0: weniger als sonst	0
1	1
2	2
3	3
4: mehr als sonst	4

high_libido

Ich hatte eine hohe <abbr title=“Lust, Geschlechtsverkehr zu haben/zu masturbieren/sexuell aktiv zu werden”>Libido</abbr>.

Distribution

Distribution of values for high_libido

1301 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	high_libido	Ich hatte eine hohe <abbr title=“Lust, Geschlechtsverkehr zu haben/zu masturbieren/sexuell aktiv zu werden”>Libido</abbr>.	0	rating_button_label_width150 blank_button			72

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

is_single

Distribution

Distribution of values for is_single

1301 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
is_single		hidden	character	1		1 - s1_demo$hetero_relationship	73	1301	0.9792	2	0	1	1	0

Item

Item options
type	name	label	optional	showif	value	item_order
hidden	is_single		1		1 - s1_demo$hetero_relationship	73

Value labels

Response choices
name	value

sexual_desire_for_whom

Ich hatte Lust mit folgender Person sexuell aktiv zu werden: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sexual_desire_for_whom

52664 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc_multiple	sexual_desire_for_whom	Ich hatte Lust mit folgender Person sexuell aktiv zu werden: <small>(Mehrfachnennungen möglich)</small>	0	mc_vertical	high_libido != 0 & is_single		74

Value labels

Response choices
name	value
1	1
2	2
3	3
4	4
5	5
6	6

sexual_initiation_self

Ich habe sexuelle Handlungen mit meinem Partner initiiert.

Distribution

Distribution of values for sexual_initiation_self

50558 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sexual_initiation_self	Ich habe sexuelle Handlungen mit meinem Partner initiiert.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.3		75

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

sexual_initiation_partner

Mein Partner hat sexuelle Handlungen mit mir initiiert.

Distribution

Distribution of values for sexual_initiation_partner

50558 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sexual_initiation_partner	Mein Partner hat sexuelle Handlungen mit mir initiiert.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & si.sexual_initiation_self		76

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

in_pair_went_out

Ich bin gemeinsam mit meinem Partner ausgegangen (Party, Kneipe, Freunde treffen, …).

Distribution

Distribution of values for in_pair_went_out

50523 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		in_pair_went_out	Ich bin gemeinsam mit meinem Partner ausgegangen <small>(Party, Kneipe, Freunde treffen, …).</small>	0	right100 left500	s1_demo$hetero_relationship & runif(1) < 0.3		77

Value labels

Response choices
name	value
Nein	0
Ja	1

extra_pair_went_out

Ich bin r ifelse(s1_demo$hetero_relationship, '__ohne__ meinen Partner', '') ausgegangen (Party, Kneipe, Freunde treffen, …).

Distribution

Distribution of values for extra_pair_went_out

44162 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		extra_pair_went_out	Ich bin `r ifelse(s1_demo$hetero_relationship, '__ohne__ meinen Partner', '')` ausgegangen <small>(Party, Kneipe, Freunde treffen, …).</small>	0	right100 left500	runif(1) < 0.3		77

Value labels

Response choices
name	value
Nein	0
Ja	1

sexual_desire_wants_desire

Ich wollte begehrt werden.

Distribution

Distribution of values for sexual_desire_wants_desire

44197 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sexual_desire_wants_desire	Ich wollte begehrt werden.	0	rating_button_label_width150 blank_button	runif(1) < 0.3		77

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

sexual_desire_fulfill_sex_needs

Ich wollte meine eigenen sexuellen Bedürfnisse erfüllen.

Distribution

Distribution of values for sexual_desire_fulfill_sex_needs

44136 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sexual_desire_fulfill_sex_needs	Ich wollte meine eigenen sexuellen Bedürfnisse erfüllen.	0	rating_button_label_width150 blank_button	runif(1) < 0.3		77

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

sexual_desire_fulfill_partner

Ich wollte, dass mein Partner sich geliebt/begehrenswert fühlt.

Distribution

Distribution of values for sexual_desire_fulfill_partner

50434 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 approval	sexual_desire_fulfill_partner	Ich wollte, dass mein Partner sich geliebt/begehrenswert fühlt.	0	rating_button_label_width150 blank_button	s1_demo$hetero_relationship & runif(1) < 0.3		77

Value labels

Response choices
name	value
0: stimmt nicht	0
1	1
2	2
3	3
4: stimmt genau	4

sexual_desire_for_activity

Ich hatte auf folgende Art von sexueller Aktivität Lust: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sexual_desire_for_activity

27802 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sexual_desire_for_activity	Ich hatte auf folgende Art von sexueller Aktivität Lust: <small>(Mehrfachnennungen möglich)</small>	0	high_libido != 0		77

Value labels

Response choices
name	value
1	kissing
2	cuddling
3	phone_skype_sex
4	sex
5	masturbation
6	masturbated_by_partner
7	masturbated_partner
8	fellatio
9	cunnilingus
10	anal_sex
11	toys
12	bdsm_sub
13	bdsm_dom
14	nothing_particular

last_had_sex

Ich hatte vor heute zuletzt mit meinem Partner Sex:

Distribution

Distribution of values for last_had_sex

58769 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		last_had_sex	Ich hatte vor heute zuletzt mit meinem Partner Sex:	0	mc_vertical	days_since_last_entry > 1 & saw_partner_last < days_since_last_entry		112

Value labels

Response choices
name	value
gestern	1
vorgestern	2
vor drei Tagen	3
vor 4 Tagen	4
vor 5 Tagen	5
vor 6 Tagen	6
vor ein bis zwei Wochen	7
vor mehr als zwei Wochen	8

sex_active

Ich war r refer_time_period sexuell aktiv (auch Selbstbefriedigung, Zärtlichkeiten)…

Distribution

Distribution of values for sex_active

1301 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		sex_active	Ich war `r refer_time_period` sexuell aktiv (auch Selbstbefriedigung, Zärtlichkeiten)…	0	right100 left500			113

Value labels

Response choices
name	value
Nein	0
Ja	1

no_sex_reason

Deshalb war ich nicht sexuell aktiv… (Mehrfachnennungen möglich)

Distribution

Distribution of values for no_sex_reason

20252 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		no_sex_reason	Deshalb war ich nicht sexuell aktiv… <small>(Mehrfachnennungen möglich)</small>	0	mc_vertical	sex_active != 1		114

Value labels

Response choices
name	value
1	just_didnt_happen
2	no_desire
3	no_time
4	had_no_partner
5	didnt_see_partner
6	partner_didnt_want_to
7	partner_couldnt
8	no_privacy
9	no_contraception
10	tired
11	felt_gross
12	felt_unattractive
13	had_pain
14	sick
15	bladder_yeast_infection
16	menstruation

sex_acts

Wie oft?

Distribution

Distribution of values for sex_acts

43716 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	min	median	max	mean	sd	hist
sex_acts	Wie oft?	number	1,any,1	numeric	0	sex_active == 1		115	right100 left500	43716	0.3024	1	1	50	1.397	0.9558	▇▁▁▁▁

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
number	1,any,1	sex_acts	Wie oft?	0	right100 left500	sex_active == 1		115

Value labels

Response choices
name	value

sex_1_time

Wann?

Distribution

Distribution of values for sex_1_time

43716 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		sex_1_time	Wann?	0	mc_vertical	sex_acts > 0		118

Value labels

Response choices
name	value
1	t0_yesterday_evening
2	t1_before_falling_asleep
3	t2_night_time
4	t3_after_waking_up
5	t4_morning
6	t5_during_day
7	t6_evening

sex_1_withwhom

Mit wem? (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_1_withwhom

43717 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_1_withwhom	Mit wem? <small>(Mehrfachnennungen möglich)</small>	0	sex_acts > 0		119

Value labels

Response choices
name	value
1	solo
2	with_partner
3	with_partner_tele
4	other_female
5	other_male

sex_1_activity

Es handelte sich um folgende sexuelle Aktivität/en: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_1_activity

43717 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_1_activity	Es handelte sich um folgende sexuelle Aktivität/en: <small>(Mehrfachnennungen möglich)</small>	0	sex_acts > 0		120

Value labels

Response choices
name	value
1	kissing
2	cuddling
3	phone_skype_sex
4	sex
5	masturbation
6	masturbated_by_partner
7	masturbated_partner
8	fellatio
9	cunnilingus
10	anal_sex
11	toys
12	bdsm_sub
13	bdsm_dom

sex_1_contraception

Ich habe folgendermaßen verhütet: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_1_contraception

51110 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		sex_1_contraception	Ich habe folgendermaßen verhütet: <small>(Mehrfachnennungen möglich)</small>	0	mc_vertical	sex_acts > 0 & sex_1_withwhom != “alleine” & sex_1_withwhom != ""		121

Value labels

Response choices
name	value
1	long_term
2	condom
3	coitus_interruptus
4	diaphragm
5	spermicide
6	counted_days
7	not_necessary
8	did_not_want
9	risked_it

sex_1_happy

Der sexuelle Akt hat mich glücklich gemacht.

Distribution

Distribution of values for sex_1_happy

43717 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_1_happy	Der sexuelle Akt hat mich glücklich gemacht.	0	rating_button_label_width150 blank_button	sex_acts > 0		122

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_1_enjoyed

Ich war sexuell befriedigt.

Distribution

Distribution of values for sex_1_enjoyed

43717 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_1_enjoyed	Ich war sexuell befriedigt.	0	rating_button_label_width150 blank_button	sex_acts > 0		123

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_1_partner_enjoyed

Mein Partner war sexuell befriedigt.

Distribution

Distribution of values for sex_1_partner_enjoyed

53082 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_1_partner_enjoyed	Mein Partner war sexuell befriedigt.	0	rating_button_label_width150 blank_button	sex_1_withwhom %contains% “Partner”		124

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_1_fantasy_partner

Gedacht habe ich dabei an … (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_1_fantasy_partner

55273 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		sex_1_fantasy_partner	Gedacht habe ich dabei an … <small>(Mehrfachnennungen möglich)</small>	0	square square120	sex_1_withwhom == “alleine”		125

Value labels

Response choices
name	value
1	partner
2	another_woman_known
3	another_man_known
4	another_woman_media
5	another_man_media
6	man_pornography
7	woman_pornography
8	nobody_in_particular
9	not_concrete

sex_1_fantasy_actions

Ich habe dabei an folgende Handlunge(n) gedacht… (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_1_fantasy_actions

55273 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_1_fantasy_actions	Ich habe dabei an folgende Handlunge(n) gedacht… <small>(Mehrfachnennungen möglich)</small>	0	sex_1_withwhom == “alleine”		126

Value labels

Response choices
name	value
1	kissing
2	cuddling
3	phone_skype_sex
4	sex
5	masturbation
6	masturbated_by_partner
7	masturbated_partner
8	fellatio
9	cunnilingus
10	anal_sex
11	toys
12	bdsm_sub
13	bdsm_dom
14	nothing_particular

sex_2_time

Wann?

Distribution

Distribution of values for sex_2_time

57491 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		sex_2_time	Wann?	0	mc_vertical	sex_acts > 1		128

Value labels

Response choices
name	value
1	t0_yesterday_evening
2	t1_before_falling_asleep
3	t2_night_time
4	t3_after_waking_up
5	t4_morning
6	t5_during_day
7	t6_evening

sex_2_withwhom

Mit wem? (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_2_withwhom

57491 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_2_withwhom	Mit wem? <small>(Mehrfachnennungen möglich)</small>	0	sex_acts > 1		129

Value labels

Response choices
name	value
1	solo
2	with_partner
3	with_partner_tele
4	other_female
5	other_male

sex_2_activity

Es handelte sich um folgende sexuelle Aktivität/en: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_2_activity

57491 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_2_activity	Es handelte sich um folgende sexuelle Aktivität/en: <small>(Mehrfachnennungen möglich)</small>	0	sex_acts > 1		130

Value labels

Response choices
name	value
1	kissing
2	cuddling
3	phone_skype_sex
4	sex
5	masturbation
6	masturbated_by_partner
7	masturbated_partner
8	fellatio
9	cunnilingus
10	anal_sex
11	toys
12	bdsm_sub
13	bdsm_dom

sex_2_contraception

Ich habe folgendermaßen verhütet: (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_2_contraception

58993 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple		sex_2_contraception	Ich habe folgendermaßen verhütet: <small>(Mehrfachnennungen möglich)</small>	0	mc_vertical	sex_acts > 1 & sex_2_withwhom != “alleine” & sex_2_withwhom != ""		131

Value labels

Response choices
name	value
1	long_term
2	condom
3	coitus_interruptus
4	diaphragm
5	spermicide
6	counted_days
7	not_necessary
8	did_not_want
9	risked_it

sex_2_happy

Der sexuelle Akt hat mich glücklich gemacht.

Distribution

Distribution of values for sex_2_happy

57491 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_2_happy	Der sexuelle Akt hat mich glücklich gemacht.	0	rating_button_label_width150 blank_button	sex_acts > 1		132

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_2_enjoyed

Ich war sexuell befriedigt.

Distribution

Distribution of values for sex_2_enjoyed

57491 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_2_enjoyed	Ich war sexuell befriedigt.	0	rating_button_label_width150 blank_button	sex_acts > 1		133

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_2_partner_enjoyed

Mein Partner war sexuell befriedigt.

Distribution

Distribution of values for sex_2_partner_enjoyed

59801 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	sex_2_partner_enjoyed	Mein Partner war sexuell befriedigt.	0	rating_button_label_width150 blank_button	sex_2_withwhom %contains% “Partner”		134

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

sex_2_fantasy_partner

Gedacht habe ich dabei an … (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_2_fantasy_partner

61164 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_multiple_button		sex_2_fantasy_partner	Gedacht habe ich dabei an … <small>(Mehrfachnennungen möglich)</small>	0	square square100	sex_2_withwhom == “alleine”		135

Value labels

Response choices
name	value
1	partner
2	another_woman_known
3	another_man_known
4	another_woman_media
5	another_man_media
6	man_pornography
7	woman_pornography
8	nobody_in_particular
9	not_concrete

sex_2_fantasy_actions

Ich habe dabei an folgende Handlunge(n) gedacht… (Mehrfachnennungen möglich)

Distribution

Distribution of values for sex_2_fantasy_actions

61164 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_multiple		sex_2_fantasy_actions	Ich habe dabei an folgende Handlunge(n) gedacht… <small>(Mehrfachnennungen möglich)</small>	0	sex_2_withwhom == “alleine”		136

Value labels

Response choices
name	value
1	kissing
2	cuddling
3	phone_skype_sex
4	sex
5	masturbation
6	masturbated_by_partner
7	masturbated_partner
8	fellatio
9	cunnilingus
10	anal_sex
11	toys
12	bdsm_sub
13	bdsm_dom
14	nothing_particular

menstrual_pain

Ich hatte <abbr title=“auch prämenstruelle”>menstruationsbedingte</abbr> Schmerzen.

Distribution

Distribution of values for menstrual_pain

11236 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
rating_button	0,4,1 not_to_a_lot	menstrual_pain	Ich hatte <abbr title=“auch prämenstruelle”>menstruationsbedingte</abbr> Schmerzen.	0	rating_button_label_width150 blank_button	s1_demo$menstruation_regular		137

Value labels

Response choices
name	value
0: überhaupt nicht	0
1	1
2	2
3	3
4: sehr viel	4

special_events_love_life

Es gab besondere nennenswerte Ereignisse hinsichtlich meines Liebeslebens:

Distribution

Distribution of values for special_events_love_life

60451 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
special_events_love_life	Es gab besondere nennenswerte Ereignisse hinsichtlich meines Liebeslebens:	textarea	character	1			138	60451	0.0353	2012	0	1	2601	8

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	special_events_love_life	Es gab besondere nennenswerte Ereignisse hinsichtlich meines Liebeslebens:	1			138

Value labels

Response choices
name	value

menstruation_since_last_entry

Ich hatte r ifelse(days_since_last_entry > 3, "seit meinem letzten Tagebucheintrag", "in den letzten 3 Tagen") menstruelle Blutungen. (Periode, nicht Zwischenblutung)

Distribution

Distribution of values for menstruation_since_last_entry

44669 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		menstruation_since_last_entry	Ich hatte `r ifelse(days_since_last_entry &gt; 3, "seit meinem letzten Tagebucheintrag", "in den letzten 3 Tagen")` menstruelle Blutungen. <small>(Periode, nicht Zwischenblutung)</small>	0	right100 left500	s1_demo$menstruation_regular & ((nrow(s3_daily) %% 3) == 0 \| days_since_last_entry > 2)		140

Value labels

Response choices
name	value
Nein	0
Ja	1

menstruation_today

Distribution

Distribution of values for menstruation_today

44669 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
menstruation_today	numeric	44669	0.2872	0	0	1	0.1686	0.3744	▇▁▁▁▂	NA

menstrual_onset

Heute war der erste Tag meiner menstruellen Blutung…

Distribution

Distribution of values for menstrual_onset

58517 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
mc_button	menstrual_onset	Heute war der erste Tag meiner menstruellen Blutung…	0	mc_vertical	menstruation_since_last_entry == 1		142

Value labels

Response choices
name	value
ja	1
nein (gestern)	2
nein (vorgestern)	3
nein (vor 3 Tagen)	4
nein (vor 4 Tagen)	5
nein (vor 5 Tagen)	6
nein (vor 6 Tagen)	7
nein (Beginn liegt noch länger zurück)	8

menstrual_onset_date

Datum der ersten menstruellen Blutung

Distribution

## 166  unique, categorical values, so not shown.

62343 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
menstrual_onset_date	Datum der ersten menstruellen Blutung	date	-2months,-6days	Date	0	menstrual_onset == 8		143	right100 left500	62343	0.0052	166	2016-05-04	2016-10-02	2017-02-11

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-2months,-6days	menstrual_onset_date	Datum der ersten menstruellen Blutung	0	right100 left500	menstrual_onset == 8		143

Value labels

Response choices
name	value

spotting

Ich hatte heute eine Zwischenblutung.

Distribution

## No non-missing values to show.

62666 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		spotting	Ich hatte heute eine Zwischenblutung.	0	right100 left500	menstruation_since_last_entry == 2		144

Value labels

Response choices
name	value
Nein	0
Ja	1

answered_honestly_today

Ich habe alles ehrlich ausgefüllt, und nicht zufällig auf Antworten geklickt. Ihnen entsteht durch Ehrlichkeit hier kein Nachteil (d. h. wir ziehen es nicht von Ihrem Guthaben ab), aber erlauben uns so, invalide Daten von unserer Untersuchung auszuschließen.

Distribution

Distribution of values for answered_honestly_today

1477 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		answered_honestly_today	Ich habe alles ehrlich ausgefüllt, und nicht zufällig auf Antworten geklickt. <small>Ihnen entsteht durch Ehrlichkeit hier kein Nachteil (d. h. wir ziehen es nicht von Ihrem Guthaben ab), aber erlauben uns so, invalide Daten von unserer Untersuchung auszuschließen.</small>	0	right100 left500			146

Value labels

Response choices
name	value
Nein	0
Ja	1

dishonest_answers

Wollen Sie uns genauer sagen, ob Sie alle Fragen falsch beantwortet haben (bspw. zufällig durchgeklickt) oder nur manche (bspw. zur Wahrung Ihrer Intimsphäre)? optional

Distribution

Distribution of values for dishonest_answers

62582 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
dishonest_answers	Wollen Sie uns genauer sagen, ob Sie alle Fragen falsch beantwortet haben (bspw. zufällig durchgeklickt) oder nur manche (bspw. zur Wahrung Ihrer Intimsphäre)? <small>optional</small>	textarea	character	1	answered_honestly_today == 0		147	62582	0.0013	73	0	4	484	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	dishonest_answers	Wollen Sie uns genauer sagen, ob Sie alle Fragen falsch beantwortet haben (bspw. zufällig durchgeklickt) oder nur manche (bspw. zur Wahrung Ihrer Intimsphäre)? <small>optional</small>	1	answered_honestly_today == 0		147

Value labels

Response choices
name	value

notes_to_us

Ich möchte dem Studienteam folgendes mitteilen: optional

Distribution

Distribution of values for notes_to_us

61321 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
notes_to_us	Ich möchte dem Studienteam folgendes mitteilen: <small>optional</small>	textarea	character	1			148	61321	0.0215	1313	0	1	1950	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	notes_to_us	Ich möchte dem Studienteam folgendes mitteilen: <small>optional</small>	1			148

Value labels

Response choices
name	value

Scale: grooming

Overview

Reliability: See details tab.

Missing: 31199.

Likert plot of scale grooming items

Distribution of scale grooming

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  2 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.82 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.87 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.09    0.08
Time             0.00    0.00
Items            0.02    0.02
ID x time        0.00    0.00
ID x items       0.85    0.71
time x items     0.00    0.00
Residual         0.23    0.19
Total            1.19    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id          0.099   0.083
id(time)    0.835   0.700
residual    0.259   0.217
total       1.193   1.000

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	class	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
grooming_1	Ich war aufgestyled.	rating_button	0,4,1 less_to_more	haven_labelled	0: weniger als sonst, 1. 1, 2. 2, 3. 3, 4. 4: mehr als sonst	0	runif(1) < 0.3		42	rating_button_label_width150 blank_button	44262	0.2937	0	2	4	1.522	1.067	5	▅▅▁▇▁▂▁▁
grooming_2	Ich habe mir Mühe mit meinem Outfit (Kleidung, Make-Up, …) gegeben.	rating_button	0,4,1 less_to_more	haven_labelled	0: weniger als sonst, 1. 1, 2. 2, 3. 3, 4. 4: mehr als sonst	0	runif(1) < 0.3		42	rating_button_label_width150 blank_button	43919	0.2992	0	2	4	1.740	1.105	5	▃▅▁▇▁▃▁▁

Scale: vanity

Overview

Reliability: See details tab.

Missing: 22002.

Likert plot of scale vanity items

Distribution of scale vanity

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  3 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.79 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.84 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.15    0.17
Time             0.00    0.00
Items            0.01    0.01
ID x time        0.00    0.00
ID x items       0.48    0.55
time x items     0.00    0.00
Residual         0.24    0.27
Total            0.89    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.16    0.17
id(time)     0.48    0.53
residual     0.27    0.30
total        0.90    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
vanity_1	Ich war mit meinem Aussehen zufrieden.	rating_button	0,4,1 less_to_more	haven_labelled	0: weniger als sonst, 1. 1, 2. 2, 3. 3, 4. 4: mehr als sonst	runif(1) < 0.3	42	rating_button_label_width150 blank_button	43996	0.2979	2	4	1.960	0.9301	5	▁▃▁▇▁▃▁▁
vanity_2	Ich habe mich gerne im Spiegel angeschaut.	rating_button	0,4,1 less_to_more	haven_labelled	0: weniger als sonst, 1. 1, 2. 2, 3. 3, 4. 4: mehr als sonst	runif(1) < 0.3	42	rating_button_label_width150 blank_button	44243	0.2940	2	4	1.850	0.9630	5	▂▃▁▇▁▃▁▁
vanity_3	Ich habe meinen Körper gerne angeschaut.	rating_button	0,4,1 less_to_more	haven_labelled	0: weniger als sonst, 1. 1, 2. 2, 3. 3, 4. 4: mehr als sonst	runif(1) < 0.3	42	rating_button_label_width150 blank_button	44235	0.2941	2	4	1.788	0.9425	5	▂▃▁▇▁▂▁▁

Scale: mate_retention

Overview

Reliability: See details tab.

Missing: 35804.

Likert plot of scale mate_retention items

Distribution of scale mate_retention

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  3 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.62 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.08 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.28 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.17    0.17
Time             0.00    0.00
Items            0.21    0.21
ID x time        0.01    0.01
ID x items       0.20    0.20
time x items     0.00    0.00
Residual         0.40    0.40
Total            1.00    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id          0.226   0.209
id(time)    0.099   0.091
residual    0.754   0.699
total       1.078   1.000

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	class	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
mate_retention1	Mein Partner war anhänglich.	rating_button	0,4,1 not_to_a_lot	haven_labelled	0: überhaupt nicht, 1. 1, 2. 2, 3. 3, 4. 4: sehr viel	0	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 64 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50253 </td> <td style="text-align:right;"> 0.1981 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.1994 </td> <td style="text-align:right;"> 1.2013 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▅▁▂▁▁ </td> </tr> <tr> <td style="text-align:left;"> mate_retention2 </td> <td style="text-align:left;"> Mein Partner war eifersüchtig. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 not_to_a_lot </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: überhaupt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: sehr viel </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3		64	rating_button_label_width150 blank_button	50434	0.1952	0	0	4	0.3143	0.7408	5	▇▁▁▁▁▁▁▁
mate_retention3	Mein Partner war besitzergreifend.	rating_button	0,4,1 not_to_a_lot	haven_labelled	0: überhaupt nicht, 1. 1, 2. 2, 3. 3, 4. 4: sehr viel	0	s1_demo$hetero_relationship & runif(1) < 0.3		64	rating_button_label_width150 blank_button	50450	0.1949	0	0	4	0.5014	0.8825	5	▇▂▁▁▁▁▁▁

Scale: in_pair_desire

Overview

Reliability: See details tab.

Missing: 26693.

Likert plot of scale in_pair_desire items

Distribution of scale in_pair_desire

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  6 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.83 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.01 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.79 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.46    0.23
Time             0.02    0.01
Items            0.27    0.14
ID x time        0.00    0.00
ID x items       0.64    0.32
time x items     0.02    0.01
Residual         0.56    0.28
Total            1.97    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.48    0.23
id(time)     0.60    0.29
residual     0.97    0.47
total        2.05    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
in_pair_desire_7	Ich habe mich zu meinem Partner hingezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50462 </td> <td style="text-align:right;"> 0.1947 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 3 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 2.580 </td> <td style="text-align:right;"> 1.246 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▂▂▁▇▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_8 </td> <td style="text-align:left;"> Ich fand meinen Partner attraktiv. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50326	0.1969	3	4	2.678	1.136	5	▂▂▁▇▁▇▁▇
in_pair_desire_10	Ich habe mich von meinem Partner sexuell angezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50426 </td> <td style="text-align:right;"> 0.1953 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.974 </td> <td style="text-align:right;"> 1.349 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▆▅▁▇▁▆▁▅ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_11 </td> <td style="text-align:left;"> Ich hatte Lust, mit meinem Partner sexuell aktiv zu werden. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50511	0.1940	2	4	1.733	1.463	5	▇▅▁▆▁▅▁▅
in_pair_desire_13	Ich hatte Fantasien über Zärtlichkeiten mit meinem Partner.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50495 </td> <td style="text-align:right;"> 0.1942 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.716 </td> <td style="text-align:right;"> 1.445 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▅▁▅▁▅▁▃ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_14 </td> <td style="text-align:left;"> Ich hatte Fantasien über Sex mit meinem Partner. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50546	0.1934	1	4	1.347	1.415	5	▇▃▁▃▁▂▁▂

Scale: extra_pair_desire

Overview

Reliability: See details tab.

Missing: 6361.

Likert plot of scale extra_pair_desire items

Distribution of scale extra_pair_desire

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  7 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.9 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.01 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.84 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.61    0.37
Time             0.01    0.00
Items            0.02    0.01
ID x time        0.00    0.00
ID x items       0.49    0.30
time x items     0.01    0.00
Residual         0.50    0.30
Total            1.64    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.63    0.36
id(time)     0.47    0.27
residual     0.65    0.37
total        1.75    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
extra_pair_desire_7	Ich habe mich zu `r anderen` Männern hingezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44116	0.2960	0	4	0.9064	1.269	5	▇▂▁▂▁▂▁▁
extra_pair_desire_8	Mir sind `r andere` attraktive Männer in meiner Umgebung aufgefallen.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44396	0.2915	1	4	1.1490	1.356	5	▇▂▁▂▁▂▁▁
extra_pair_desire_10	Ich habe mich von einem `r anderen` Mann sexuell angezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44482	0.2902	0	4	0.7700	1.251	5	▇▂▁▁▁▁▁▁
extra_pair_desire_11	Ich hatte Lust mit einem `r anderen` Mann sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44375	0.2919	0	4	0.7612	1.271	5	▇▁▁▁▁▁▁▁
extra_pair_desire_13	Ich hatte Fantasien über Zärtlichkeiten mit einem `r anderen` Mann.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44457	0.2906	0	4	0.8813	1.354	5	▇▁▁▁▁▁▁▁
extra_pair_desire_14	Ich hatte Fantasien über Sex mit einem `r anderen` Mann.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44095	0.2963	0	4	0.7374	1.282	5	▇▁▁▁▁▁▁▁
extra_pair_desire_16	Ich habe mir Gedanken über `r andere` potentielle Partner gemacht.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44023	0.2975	0	4	1.0375	1.394	5	▇▂▁▂▁▂▁▁

weekday

Distribution

Distribution of values for weekday

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
weekday	factor	FALSE	Monday, 2. Tuesday, 3. Wednesday, 4. Thursday, 5. Friday, 6. Saturday, 7. Sunday	0	1	7	Mon: 9241, Tue: 9189, Wed: 9137, Sun: 9131	NA

weekend

Distribution

Distribution of values for weekend

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
weekend	numeric	0	1	0	0	1	0.4159	0.4929	▇▁▁▁▆	NA

sleep_duration

Distribution

Distribution of values for sleep_duration

31917 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
sleep_duration	numeric	31917	0.4907	0	8	24	7.921	2.034	▁▇▁▁▁	NA

first_diary_day

Distribution

## 208  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
first_diary_day	Date	0	1	208	2016-05-03	2016-09-20	2017-01-15	NA

progesterone_mean

Distribution

Distribution of values for progesterone_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
progesterone_mean	numeric	55406	0.1159	2.5	43	141	44.17	29.72	▇▇▅▂▁	NA

progesterone_diff

Distribution

Distribution of values for progesterone_diff

62335 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
progesterone_diff	numeric	62335	0.0053	-129	-5.8	156	0.2956	52.46	▂▆▇▂▁	NA

progesterone_log_mean

Distribution

Distribution of values for progesterone_log_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
progesterone_log_mean	numeric	55406	0.1159	0.91	2.8	4.7	2.75	0.7464	▂▃▇▅▁	NA

progesterone_log_diff

Distribution

Distribution of values for progesterone_log_diff

62335 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
progesterone_log_diff	numeric	62335	0.0053	-2.8	-0.13	3.1	-0.0089	1.356	▃▇▆▆▂	NA

estradiol_mean

Distribution

Distribution of values for estradiol_mean

58567 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
estradiol_mean	numeric	58567	0.0654	2.9	6.8	57	10.62	9.918	▇▁▁▁▁	NA

estradiol_diff

Distribution

Distribution of values for estradiol_diff

62594 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
estradiol_diff	numeric	62594	0.0011	-11	0	10	-0.1614	2.983	▁▁▇▁▁	NA

estradiol_log_mean

Distribution

Distribution of values for estradiol_log_mean

58567 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
estradiol_log_mean	numeric	58567	0.0654	1.1	1.9	4	2.055	0.6793	▇▇▅▂▁	NA

estradiol_log_diff

Distribution

Distribution of values for estradiol_log_diff

62594 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
estradiol_log_diff	numeric	62594	0.0011	-0.95	0	1.2	-0.0111	0.3315	▁▂▇▁▁	NA

ibl_estradiol_mean

Distribution

Distribution of values for ibl_estradiol_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
ibl_estradiol_mean	numeric	55406	0.1159	1.7	5.3	14	5.675	2.388	▅▇▅▂▁	NA

ibl_estradiol_diff

Distribution

Distribution of values for ibl_estradiol_diff

62330 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
ibl_estradiol_diff	numeric	62330	0.0054	-6.8	-0.26	8.7	-0.0642	2.44	▁▇▇▂▁	NA

ibl_estradiol_log_mean

Distribution

Distribution of values for ibl_estradiol_log_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
ibl_estradiol_log_mean	numeric	55406	0.1159	-0.029	1.5	2.6	1.55	0.4578	▁▂▇▆▂	NA

ibl_estradiol_log_diff

Distribution

Distribution of values for ibl_estradiol_log_diff

62330 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
ibl_estradiol_log_diff	numeric	62330	0.0054	-2.4	0.00027	1.2	-0.0137	0.4893	▁▁▃▇▂	NA

testosterone_mean

Distribution

Distribution of values for testosterone_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
testosterone_mean	numeric	55406	0.1159	1.8	7.2	25	7.739	3.418	▆▇▂▁▁	NA

testosterone_diff

Distribution

Distribution of values for testosterone_diff

62323 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
testosterone_diff	numeric	62323	0.0055	-6.6	-0.12	14	0.0226	2.379	▂▇▂▁▁	NA

testosterone_log_mean

Distribution

Distribution of values for testosterone_log_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
testosterone_log_mean	numeric	55406	0.1159	0.58	1.9	3.2	1.911	0.4465	▁▃▇▅▁	NA

testosterone_log_diff

Distribution

Distribution of values for testosterone_log_diff

62323 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
testosterone_log_diff	numeric	62323	0.0055	-1.1	0.0045	0.92	0.0026	0.2817	▁▂▇▅▁	NA

cortisol_mean

Distribution

Distribution of values for cortisol_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cortisol_mean	numeric	55406	0.1159	0.94	3.2	10	3.634	1.832	▇▆▃▁▁	NA

cortisol_diff

Distribution

Distribution of values for cortisol_diff

62312 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cortisol_diff	numeric	62312	0.0056	-4.8	-0.22	7.6	-0.0472	1.725	▁▇▅▁▁	NA

cortisol_log_mean

Distribution

Distribution of values for cortisol_log_mean

55406 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cortisol_log_mean	numeric	55406	0.1159	-0.064	1.1	2.3	1.061	0.4778	▂▇▇▃▂	NA

cortisol_log_diff

Distribution

Distribution of values for cortisol_log_diff

62312 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cortisol_log_diff	numeric	62312	0.0056	-3	-0.0094	1.6	-0.0061	0.4854	▁▁▃▇▁	NA

window_length

Distribution

Distribution of values for window_length

62121 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
window_length	numeric	62121	0.0087	1	5	66	6.932	7.471	▇▁▁▁▁	NA

date_of_ovulation_awareness

Distribution

## 164  unique, categorical values, so not shown.

62359 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_awareness	Date	62359	0.0049	164	2016-05-19	2016-10-17	2017-02-16	NA

diary_day_observation

Distribution

Distribution of values for diary_day_observation

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
diary_day_observation	character	0	1	4	0	8	20	0	NA

next_menstrual_onset

Distribution

## 303  unique, categorical values, so not shown.

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
next_menstrual_onset	Date	17350	0.7231	303	2016-05-09	2016-10-31	2017-04-20	NA

last_menstrual_onset

Distribution

## 304  unique, categorical values, so not shown.

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
last_menstrual_onset	Date	10236	0.8367	304	2016-04-02	2016-09-28	2017-03-23	NA

menstrual_onset_days_until

Distribution

Distribution of values for menstrual_onset_days_until

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
menstrual_onset_days_until	numeric	17350	0.7231	-291	-14	-1	-15.88	13.62	▁▁▁▁▇	NA

menstrual_onset_days_since

Distribution

Distribution of values for menstrual_onset_days_since

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
menstrual_onset_days_since	numeric	10236	0.8367	0	14	188	15.29	10.76	▇▁▁▁▁	NA

date_origin

Distribution

Distribution of values for date_origin

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
date_origin	character	0	1	4	0	3	9	0	NA

menstruation_labelled

Distribution

Distribution of values for menstruation_labelled

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
menstruation_labelled	factor	FALSE	yes, 2. probably, 3. no	0	1	3	no: 52773, pro: 5743, yes: 4150	NA

next_menstrual_onset_if_no_last

Distribution

## No non-missing values to show.

62666 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	label
next_menstrual_onset_if_no_last	Date	62666	0	0	NA

day_number

Distribution

Distribution of values for day_number

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
day_number	numeric	0	1	0	30	70	31.44	20.28	▇▆▆▅▅	NA

number_of_cycles

Distribution

Distribution of values for number_of_cycles

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
number_of_cycles	numeric	10236	0.8367	1	4	7	3.657	0.8565	▁▃▇▂▁	NA

cycle_nr

Distribution

Distribution of values for cycle_nr

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cycle_nr	numeric	10236	0.8367	1	2	5	2.096	0.8484	▅▇▅▁▁	NA

cycle_length

Distribution

Distribution of values for cycle_length

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cycle_length	numeric	17350	0.7231	7	29	292	31.6	12.85	▇▁▁▁▁	NA

cycle_nr_fully_observed

Distribution

Distribution of values for cycle_nr_fully_observed

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
cycle_nr_fully_observed	numeric	10236	0.8367	0	3	5	2.629	0.8459	▁▅▇▁▁	NA

mean_cycle_length_diary

Distribution

Distribution of values for mean_cycle_length_diary

11376 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
mean_cycle_length_diary	numeric	11376	0.8185	13	28	266	31.05	10.52	▇▁▁▁▁	NA

median_cycle_length_diary

Distribution

Distribution of values for median_cycle_length_diary

11376 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
median_cycle_length_diary	numeric	11376	0.8185	14	28	266	30.83	10.42	▇▁▁▁▁	NA

next_menstrual_onset_inferred

Distribution

## 302  unique, categorical values, so not shown.

10330 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
next_menstrual_onset_inferred	Date	10330	0.8352	302	2016-05-05	2016-10-26	2017-04-20	NA

RCD_inferred

Distribution

Distribution of values for RCD_inferred

10330 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_inferred	numeric	10330	0.8352	-50	-14	160	-13.32	10.88	▇▃▁▁▁	NA

luteal_BC

Distribution

Distribution of values for luteal_BC

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
luteal_BC	numeric	17350	0.7231	0	1	1	0.5437	0.4981	▇▁▁▁▇	NA

follicular_FC

Distribution

Distribution of values for follicular_FC

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
follicular_FC	numeric	10236	0.8367	0	1	1	0.5385	0.4985	▇▁▁▁▇	NA

day_lh_surge

Distribution

Distribution of values for day_lh_surge

62513 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
day_lh_surge	numeric	62513	0.0024	1	1	1	1	0	▁▁▇▁▁	NA

day_of_ovulation

Distribution

Distribution of values for day_of_ovulation

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
day_of_ovulation	numeric	17350	0.7231	0	0	1	0.0341	0.1814	▇▁▁▁▁	NA

day_of_ovulation_inferred

Distribution

Distribution of values for day_of_ovulation_inferred

10330 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
day_of_ovulation_inferred	numeric	10330	0.8352	0	0	1	0.0338	0.1808	▇▁▁▁▁	NA

day_of_ovulation_forward_counted

Distribution

Distribution of values for day_of_ovulation_forward_counted

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
day_of_ovulation_forward_counted	numeric	10236	0.8367	0	0	1	0.0337	0.1805	▇▁▁▁▁	NA

date_of_ovulation_BC

Distribution

## 271  unique, categorical values, so not shown.

21945 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_BC	Date	21945	0.6498	271	2016-05-05	2016-10-17	2017-03-12	NA

date_of_ovulation_inferred

Distribution

## 268  unique, categorical values, so not shown.

17520 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_inferred	Date	17520	0.7204	268	2016-05-12	2016-10-14	2017-03-11	NA

date_of_ovulation_forward_counted

Distribution

## 269  unique, categorical values, so not shown.

17292 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_forward_counted	Date	17292	0.7241	269	2016-05-07	2016-10-16	2017-03-12	NA

date_of_ovulation_LH

Distribution

## 131  unique, categorical values, so not shown.

58430 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_LH	Date	58430	0.0676	131	2016-05-15	2016-10-21	2017-03-17	NA

DRLH

Distribution

Distribution of values for DRLH

58705 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
DRLH	numeric	58705	0.0632	-15	1	15	0.51	7.929	▆▇▇▇▆	NA

date_of_ovulation_awareness_nr

Distribution

Distribution of values for date_of_ovulation_awareness_nr

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
date_of_ovulation_awareness_nr	numeric	0	1	0	0	3	0.2085	0.442	▇▂▁▁▁	NA

fertile_awareness

Distribution

Distribution of values for fertile_awareness

62359 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_awareness	numeric	62359	0.0049	1	1	1	1	0	▁▁▇▁▁	NA

date_of_ovulation_avg_follicular

Distribution

## 217  unique, categorical values, so not shown.

52392 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_avg_follicular	Date	52392	0.1639	217	2016-04-26	2016-09-27	2017-03-13	NA

date_of_ovulation_avg_luteal

Distribution

## 207  unique, categorical values, so not shown.

54213 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_avg_luteal	Date	54213	0.1349	207	2016-04-28	2016-09-27	2017-03-09	NA

date_of_ovulation_avg_luteal_inferred

Distribution

## 209  unique, categorical values, so not shown.

53034 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
date_of_ovulation_avg_luteal_inferred	Date	53034	0.1537	209	2016-04-29	2016-09-27	2017-02-16	NA

FCD

Distribution

Distribution of values for FCD

10236 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
FCD	numeric	10236	0.8367	1	15	189	16.29	10.76	▇▁▁▁▁	NA

RCD

Distribution

Distribution of values for RCD

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD	numeric	17350	0.7231	-291	-14	-1	-15.88	13.62	▁▁▁▁▇	NA

DAL

Distribution

Distribution of values for DAL

54213 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
DAL	numeric	54213	0.1349	-182	0	20	-1.075	11.12	▁▁▁▁▇	NA

RCD_squished

Distribution

Distribution of values for RCD_squished

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_squished	numeric	18575	0.7036	-29	-14	-1	-14.12	8.168	▆▆▆▇▇	NA

RCD_squished_rounded

Distribution

Distribution of values for RCD_squished_rounded

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_squished_rounded	numeric	18575	0.7036	-29	-14	-1	-14.12	8.172	▆▇▆▇▇	NA

RCD_inferred_squished

Distribution

Distribution of values for RCD_inferred_squished

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_inferred_squished	numeric	14955	0.7614	-29	-15	-1	-15.37	8.098	▇▇▆▇▆	NA

RCD_rel_to_ovulation

Distribution

Distribution of values for RCD_rel_to_ovulation

17350 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_rel_to_ovulation	numeric	17350	0.7231	-276	1	14	-0.8777	13.62	▁▁▁▁▇	NA

RCD_fab

Distribution

Distribution of values for RCD_fab

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
RCD_fab	numeric	18575	0.7036	-29	-14	-1	-14.12	8.168	▆▆▆▇▇	NA

conception_risk_lh

Distribution

Distribution of values for conception_risk_lh

61027 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
conception_risk_lh	numeric	61027	0.0262	0	0.06	0.25	0.101	0.0928	▇▃▁▃▃	NA

fertile_lh

Distribution

Distribution of values for fertile_lh

58705 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_lh	numeric	58705	0.0632	0	0	1	0.1671	0.3108	▇▁▁▁▁	NA

prc_stirn_b

Distribution

Distribution of values for prc_stirn_b

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b	numeric	18575	0.7036	0.01	0.07	0.58	0.1726	0.1944	▇▂▁▁▂	NA

prc_wcx_b

Distribution

Distribution of values for prc_wcx_b

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b	numeric	18575	0.7036	0	0.016	0.094	0.0308	0.0309	▇▂▁▂▂	NA

fertile_narrow

Distribution

Distribution of values for fertile_narrow

40036 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow	numeric	40036	0.3611	0.053	0.053	0.51	0.2078	0.2161	▇▁▁▁▅	NA

fertile_broad

Distribution

Distribution of values for fertile_broad

34137 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad	numeric	34137	0.4553	0.053	0.053	0.44	0.237	0.1931	▇▁▁▁▇	NA

fertile_window

Distribution

Distribution of values for fertile_window

34137 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window	factor	FALSE	infertile, 2. broad, 3. narrow	34137	0.4553	3	inf: 14976, nar: 7654, bro: 5899	NA

premenstrual_phase

Distribution

Distribution of values for premenstrual_phase

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase	logical	18575	0.7036	FAL: 33940, TRU: 10151	0.2302	NA

prc_stirn_b_squished

Distribution

Distribution of values for prc_stirn_b_squished

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b_squished	numeric	18575	0.7036	0.01	0.07	0.58	0.1782	0.1956	▇▂▁▁▂	NA

prc_wcx_b_squished

Distribution

Distribution of values for prc_wcx_b_squished

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b_squished	numeric	18575	0.7036	0	0.018	0.094	0.0315	0.0311	▇▂▁▂▂	NA

fertile_narrow_squished

Distribution

Distribution of values for fertile_narrow_squished

39753 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow_squished	numeric	39753	0.3656	0.053	0.053	0.51	0.2115	0.2173	▇▁▁▁▅	NA

fertile_broad_squished

Distribution

Distribution of values for fertile_broad_squished

33636 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad_squished	numeric	33636	0.4632	0.053	0.053	0.44	0.2405	0.1932	▇▁▁▁▇	NA

fertile_window_squished

Distribution

Distribution of values for fertile_window_squished

33636 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window_squished	factor	FALSE	infertile, 2. broad, 3. narrow	33636	0.4632	3	inf: 14976, nar: 7937, bro: 6117	NA

premenstrual_phase_squished

Distribution

Distribution of values for premenstrual_phase_squished

18575 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase_squished	logical	18575	0.7036	FAL: 33940, TRU: 10151	0.2302	NA

prc_stirn_b_inferred_squished

Distribution

Distribution of values for prc_stirn_b_inferred_squished

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b_inferred_squished	numeric	14955	0.7614	0.01	0.09	0.58	0.1826	0.1957	▇▂▁▁▂	NA

prc_wcx_b_inferred_squished

Distribution

Distribution of values for prc_wcx_b_inferred_squished

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b_inferred_squished	numeric	14955	0.7614	0	0.018	0.094	0.0318	0.0314	▇▂▁▂▂	NA

fertile_narrow_inferred_squished

Distribution

Distribution of values for fertile_narrow_inferred_squished

39124 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow_inferred_squished	numeric	39124	0.3757	0.053	0.053	0.51	0.2224	0.2205	▇▁▁▁▅	NA

fertile_broad_inferred_squished

Distribution

Distribution of values for fertile_broad_inferred_squished

32218 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad_inferred_squished	numeric	32218	0.4859	0.053	0.44	0.44	0.2517	0.1933	▇▁▁▁▇	NA

fertile_window_inferred_squished

Distribution

Distribution of values for fertile_window_inferred_squished

32218 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window_inferred_squished	factor	FALSE	infertile, 2. broad, 3. narrow	32218	0.4859	3	inf: 14824, nar: 8718, bro: 6906	NA

premenstrual_phase_inferred_squished

Distribution

Distribution of values for premenstrual_phase_inferred_squished

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase_inferred_squished	logical	14955	0.7614	FAL: 39255, TRU: 8456	0.1772	NA

prc_stirn_b_forward_counted

Distribution

Distribution of values for prc_stirn_b_forward_counted

11543 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b_forward_counted	numeric	11543	0.8158	0.01	0.07	0.58	0.1751	0.1952	▇▂▁▁▂	NA

prc_wcx_b_forward_counted

Distribution

Distribution of values for prc_wcx_b_forward_counted

11543 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b_forward_counted	numeric	11543	0.8158	0	0.016	0.094	0.0305	0.0313	▇▂▁▂▂	NA

fertile_narrow_forward_counted

Distribution

Distribution of values for fertile_narrow_forward_counted

38745 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow_forward_counted	numeric	38745	0.3817	0.053	0.053	0.51	0.2235	0.2208	▇▁▁▁▅	NA

fertile_broad_forward_counted

Distribution

Distribution of values for fertile_broad_forward_counted

31648 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad_forward_counted	numeric	31648	0.495	0.053	0.44	0.44	0.2529	0.1932	▇▁▁▁▇	NA

fertile_window_forward_counted

Distribution

Distribution of values for fertile_window_forward_counted

31648 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window_forward_counted	factor	FALSE	infertile, 2. broad, 3. narrow	31648	0.495	3	inf: 15006, nar: 8915, bro: 7097	NA

premenstrual_phase_forward_counted

Distribution

Distribution of values for premenstrual_phase_forward_counted

11543 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase_forward_counted	logical	11543	0.8158	FAL: 42466, TRU: 8657	0.1693	NA

prc_stirn_b_aware_luteal

Distribution

Distribution of values for prc_stirn_b_aware_luteal

54504 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b_aware_luteal	numeric	54504	0.1302	0.01	0.07	0.58	0.177	0.1956	▇▂▁▁▂	NA

prc_wcx_b_aware_luteal

Distribution

Distribution of values for prc_wcx_b_aware_luteal

54504 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b_aware_luteal	numeric	54504	0.1302	0	0.016	0.094	0.0314	0.0312	▇▂▁▂▂	NA

fertile_narrow_aware_luteal

Distribution

Distribution of values for fertile_narrow_aware_luteal

58554 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow_aware_luteal	numeric	58554	0.0656	0.053	0.053	0.51	0.2158	0.2187	▇▁▁▁▅	NA

fertile_broad_aware_luteal

Distribution

Distribution of values for fertile_broad_aware_luteal

57436 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad_aware_luteal	numeric	57436	0.0835	0.053	0.053	0.44	0.2442	0.1933	▇▁▁▁▇	NA

fertile_window_aware_luteal

Distribution

Distribution of values for fertile_window_aware_luteal

57436 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window_aware_luteal	factor	FALSE	infertile, 2. broad, 3. narrow	57436	0.0835	3	inf: 2649, nar: 1463, bro: 1118	NA

premenstrual_phase_aware_luteal

Distribution

Distribution of values for premenstrual_phase_aware_luteal

54504 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase_aware_luteal	logical	54504	0.1302	FAL: 6599, TRU: 1563	0.1915	NA

prc_stirn_b_inferred

Distribution

Distribution of values for prc_stirn_b_inferred

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_stirn_b_inferred	numeric	14955	0.7614	0.01	0.09	0.58	0.1852	0.1967	▇▂▁▁▃	NA

prc_wcx_b_inferred

Distribution

Distribution of values for prc_wcx_b_inferred

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prc_wcx_b_inferred	numeric	14955	0.7614	0	0.018	0.094	0.0323	0.0315	▇▂▁▂▂	NA

fertile_narrow_inferred

Distribution

Distribution of values for fertile_narrow_inferred

39014 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_narrow_inferred	numeric	39014	0.3774	0.053	0.053	0.51	0.2238	0.2209	▇▁▁▁▅	NA

fertile_broad_inferred

Distribution

Distribution of values for fertile_broad_inferred

31969 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
fertile_broad_inferred	numeric	31969	0.4899	0.053	0.44	0.44	0.2533	0.1932	▇▁▁▁▇	NA

fertile_window_inferred

Distribution

Distribution of values for fertile_window_inferred

31969 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
fertile_window_inferred	factor	FALSE	infertile, 2. broad, 3. narrow	31969	0.4899	3	inf: 14824, nar: 8828, bro: 7045	NA

premenstrual_phase_inferred

Distribution

Distribution of values for premenstrual_phase_inferred

14955 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
premenstrual_phase_inferred	logical	14955	0.7614	FAL: 39255, TRU: 8456	0.1772	NA

fertile_fab

Est. fertile window prob. (BC+i)

Distribution

Distribution of values for fertile_fab

18575 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
fertile_fab	Est. fertile window prob. (BC+i)	numeric	18575	0.7036	0.01	0.07	0.58	0.1726	0.1944	▇▂▁▁▂

premenstrual_phase_fab

Est. premenstrual phase (BC+i)

Distribution

Distribution of values for premenstrual_phase_fab

18575 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	count	mean
premenstrual_phase_fab	Est. premenstrual phase (BC+i)	logical	18575	0.7036	FAL: 33940, TRU: 10151	0.2302

menstruation_imputed

Distribution

Distribution of values for menstruation_imputed

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
menstruation_imputed	numeric	0	1	0.000000035	0.0017	1	0.1413	0.3028	▇▁▁▁▁	NA

menstruation

Est. menstruation

Distribution

Distribution of values for menstruation

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
menstruation	Est. menstruation	numeric	0	1	0	0.0002	1	0.1411	0.3191	▇▁▁▁▁

Scale: extra_pair_desire_and_behaviour

Overview

Reliability: See details tab.

Missing: 1616.

Likert plot of scale extra_pair_desire_and_behaviour items

Distribution of scale extra_pair_desire_and_behaviour

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  15 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.91 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.12 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.8 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.47    0.26
Time             0.00    0.00
Items            0.34    0.18
ID x time        0.01    0.00
ID x items       0.37    0.20
time x items     0.00    0.00
Residual         0.63    0.35
Total            1.82    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.49    0.23
id(time)     0.34    0.16
residual     1.26    0.60
total        2.09    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
extra_pair_desire_1	Ich habe an einen `r anderen` Mann gedacht.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44311	0.2929	0	4	1.2740	1.518	5	▇▂▁▂▁▂▁▂
extra_pair_desire_2R	Ich hatte keine Lust, Zeit mit `r anderen` Männern zu verbringen.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 3. 1, 2. 2, 1. 3, 0. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	43971	0.2983	2	4	1.7023	1.610	5	▇▂▁▃▁▂▁▅
extra_pair_desire_3R	Es war mir egal, ob mich `r andere` Männer als attraktiv wahrnehmen.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 3. 1, 2. 2, 1. 3, 0. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44212	0.2945	2	4	2.0392	1.489	5	▇▅▁▆▁▇▁▇
extra_pair_desire_4	Mich haben `r andere` Männer angeflirtet.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44315	0.2928	0	4	0.7981	1.207	5	▇▂▁▂▁▁▁▁
extra_pair_desire_6	Ich habe mit `r anderen` Männern geflirtet.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44261	0.2937	0	4	0.5989	1.078	5	▇▂▁▁▁▁▁▁
extra_pair_desire_7	Ich habe mich zu `r anderen` Männern hingezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44116	0.2960	0	4	0.9064	1.269	5	▇▂▁▂▁▂▁▁
extra_pair_desire_8	Mir sind `r andere` attraktive Männer in meiner Umgebung aufgefallen.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44396	0.2915	1	4	1.1490	1.356	5	▇▂▁▂▁▂▁▁
extra_pair_desire_9	`r andere_uc` Männer fanden mich attraktiv.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44331	0.2926	2	4	1.4719	1.241	5	▇▃▁▇▁▃▁▂
extra_pair_desire_10	Ich habe mich von einem `r anderen` Mann sexuell angezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44482	0.2902	0	4	0.7700	1.251	5	▇▂▁▁▁▁▁▁
extra_pair_desire_11	Ich hatte Lust mit einem `r anderen` Mann sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44375	0.2919	0	4	0.7612	1.271	5	▇▁▁▁▁▁▁▁
extra_pair_desire_12	Ein `r anderer` Mann schien Lust zu haben, mit mir sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44370	0.2920	0	4	0.7033	1.205	5	▇▁▁▁▁▁▁▁
extra_pair_desire_13	Ich hatte Fantasien über Zärtlichkeiten mit einem `r anderen` Mann.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44457	0.2906	0	4	0.8813	1.354	5	▇▁▁▁▁▁▁▁
extra_pair_desire_14	Ich hatte Fantasien über Sex mit einem `r anderen` Mann.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44095	0.2963	0	4	0.7374	1.282	5	▇▁▁▁▁▁▁▁
extra_pair_desire_5R	`r andere_uc` Männer haben mich ignoriert.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 3. 1, 2. 2, 1. 3, 0. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44296	0.2931	3	4	2.7059	1.237	5	▂▂▁▆▁▅▁▇
extra_pair_desire_16	Ich habe mir Gedanken über `r andere` potentielle Partner gemacht.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44023	0.2975	0	4	1.0375	1.394	5	▇▂▁▂▁▂▁▁

Scale: extra_pair_interest

Overview

Reliability: See details tab.

Missing: 16022.

Likert plot of scale extra_pair_interest items

Distribution of scale extra_pair_interest

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  4 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.77 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.01 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.31 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.34    0.16
Time             0.00    0.00
Items            0.83    0.39
ID x time        0.00    0.00
ID x items       0.42    0.20
time x items     0.00    0.00
Residual         0.53    0.25
Total            2.12    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.39   0.184
id(time)     0.18   0.083
residual     1.57   0.733
total        2.14   1.000

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
extra_pair_desire_4	Mich haben `r andere` Männer angeflirtet.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44315	0.2928	0	4	0.7981	1.207	5	▇▂▁▂▁▁▁▁
extra_pair_desire_9	`r andere_uc` Männer fanden mich attraktiv.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44331	0.2926	2	4	1.4719	1.241	5	▇▃▁▇▁▃▁▂
extra_pair_desire_12	Ein `r anderer` Mann schien Lust zu haben, mit mir sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44370	0.2920	0	4	0.7033	1.205	5	▇▁▁▁▁▁▁▁
extra_pair_desire_5R	`r andere_uc` Männer haben mich ignoriert.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 3. 1, 2. 2, 1. 3, 0. 4: stimmt genau	runif(1) < 0.3	77	rating_button_label_width150 blank_button	44296	0.2931	3	4	2.7059	1.237	5	▂▂▁▆▁▅▁▇

Scale: in_pair_desire_and_behaviour

Overview

Reliability: See details tab.

Missing: 22257.

Likert plot of scale in_pair_desire_and_behaviour items

Distribution of scale in_pair_desire_and_behaviour

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  14 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.81 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.17 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.79 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.32    0.16
Time             0.02    0.01
Items            0.50    0.26
ID x time        0.01    0.00
ID x items       0.42    0.21
time x items     0.02    0.01
Residual         0.68    0.34
Total            1.96    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.33    0.15
id(time)     0.39    0.18
residual     1.42    0.66
total        2.14    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	showif	item_order	class	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
in_pair_desire_1	Ich habe an meinen Partner gedacht.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50542 </td> <td style="text-align:right;"> 0.1935 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 3 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 2.935 </td> <td style="text-align:right;"> 1.1375 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▁▁▁▅▁▆▁▇ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_2R </td> <td style="text-align:left;"> Ich hatte __keine__ Lust, Zeit mit meinem Partner zu verbringen. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 4. 0: stimmt nicht,<br>3. 1,<br>2. 2,<br>1. 3,<br>0. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50608	0.1924	4	4	3.371	1.1297	5	▁▁▁▁▁▁▁▇
in_pair_desire_3R	Es war mir egal, ob mich mein Partner als attraktiv wahrnimmt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 3. 1, 2. 2, 1. 3, 0. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50580 </td> <td style="text-align:right;"> 0.1929 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 3 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 2.982 </td> <td style="text-align:right;"> 1.2347 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▁▁▁▃▁▃▁▇ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_4 </td> <td style="text-align:left;"> Mein Partner hat mit mir geflirtet. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50371	0.1962	2	4	1.589	1.3775	5	▇▅▁▆▁▅▁▃
in_pair_desire_6	Ich habe mit meinem Partner geflirtet.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50429 </td> <td style="text-align:right;"> 0.1953 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.558 </td> <td style="text-align:right;"> 1.3788 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▅▁▅▁▂ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_7 </td> <td style="text-align:left;"> Ich habe mich zu meinem Partner hingezogen gefühlt. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50462	0.1947	3	4	2.580	1.2463	5	▂▂▁▇▁▇▁▇
in_pair_desire_8	Ich fand meinen Partner attraktiv.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50326 </td> <td style="text-align:right;"> 0.1969 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 3 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 2.678 </td> <td style="text-align:right;"> 1.1362 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▂▂▁▇▁▇▁▇ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_9 </td> <td style="text-align:left;"> Mein Partner fand mich attraktiv. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50479	0.1945	2	4	2.458	1.0858	5	▁▁▁▇▁▅▁▃
in_pair_desire_10	Ich habe mich von meinem Partner sexuell angezogen gefühlt.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50426 </td> <td style="text-align:right;"> 0.1953 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.974 </td> <td style="text-align:right;"> 1.3490 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▆▅▁▇▁▆▁▅ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_11 </td> <td style="text-align:left;"> Ich hatte Lust, mit meinem Partner sexuell aktiv zu werden. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50511	0.1940	2	4	1.733	1.4629	5	▇▅▁▆▁▅▁▅
in_pair_desire_12	Mein Partner schien Lust zu haben, mit mir sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50617 </td> <td style="text-align:right;"> 0.1923 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.802 </td> <td style="text-align:right;"> 1.5317 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▅▁▃▁▆ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_13 </td> <td style="text-align:left;"> Ich hatte Fantasien über Zärtlichkeiten mit meinem Partner. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50495	0.1942	2	4	1.716	1.4450	5	▇▅▁▅▁▅▁▃
in_pair_desire_14	Ich hatte Fantasien über Sex mit meinem Partner.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50546 </td> <td style="text-align:right;"> 0.1934 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 1 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.347 </td> <td style="text-align:right;"> 1.4147 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▃▁▂▁▂ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_5R </td> <td style="text-align:left;"> Mein Partner hat mich ignoriert. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 4. 0: stimmt nicht,<br>3. 1,<br>2. 2,<br>1. 3,<br>0. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3	77	rating_button_label_width150 blank_button	50403	0.1957	4	4	3.480	0.9883	5	▁▁▁▁▁▂▁▇

Scale: in_pair_interest

Overview

Reliability: See details tab.

Missing: 31709.

Likert plot of scale in_pair_interest items

Distribution of scale in_pair_interest

Reliability details


Multilevel Generalizability analysis   
Call: psych::multilevel.reliability(x = long_rel, grp = "session", 
    Time = "day_number", items = "variable", aov = FALSE, lmer = TRUE, 
    lme = FALSE, long = TRUE, values = "value")

The data had  1373  observations taken over  60544  time intervals for  4 items.

 Alternative estimates of reliability based upon Generalizability theory

RkF  =  1 Reliability of average of all ratings across all items and  times (Fixed time effects)
R1R  =  0.66 Generalizability of a single time point across all items (Random time effects)
RkR  =  1 Generalizability of average time points across all items (Random time effects)
Rc   =  0.01 Generalizability of change (fixed time points, fixed items) 
RkRn =  1 Generalizability of between person differences averaged over time (time nested within people)
Rcn  =  0.41 Generalizability of within person variations averaged over items  (time nested within people)

 These reliabilities are derived from the components of variance estimated by lmer 
             variance Percent
ID               0.27    0.13
Time             0.04    0.02
Items            0.71    0.33
ID x time        0.00    0.00
ID x items       0.46    0.21
time x items     0.04    0.02
Residual         0.64    0.30
Total            2.16    1.00

 The nested components of variance estimated from lmer are:
         variance Percent
id           0.32    0.15
id(time)     0.27    0.13
residual     1.55    0.72
total        2.15    1.00

To see the ANOVA and alpha by subject, use the short = FALSE option.
 To see the summaries of the ICCs by subject and time, use all=TRUE
 To see specific objects select from the following list:
 ANOVA s.lmer s.lme alpha summary.by.person summary.by.time ICC.by.person ICC.by.time lmer long Call

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	class	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
in_pair_desire_4	Mein Partner hat mit mir geflirtet.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	0	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50371 </td> <td style="text-align:right;"> 0.1962 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.589 </td> <td style="text-align:right;"> 1.3775 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▅▁▆▁▅▁▃ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_9 </td> <td style="text-align:left;"> Mein Partner fand mich attraktiv. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 0. 0: stimmt nicht,<br>1. 1,<br>2. 2,<br>3. 3,<br>4. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3		77	rating_button_label_width150 blank_button	50479	0.1945	0	2	4	2.458	1.0858	5	▁▁▁▇▁▅▁▃
in_pair_desire_12	Mein Partner schien Lust zu haben, mit mir sexuell aktiv zu werden.	rating_button	0,4,1 approval	haven_labelled	0: stimmt nicht, 1. 1, 2. 2, 3. 3, 4. 4: stimmt genau	0	s1_demo\(hetero_relationship & runif(1) < 0.3 </td> <td style="text-align:left;"> </td> <td style="text-align:left;"> 77 </td> <td style="text-align:left;"> rating_button_label_width150 blank_button </td> <td style="text-align:right;"> 50617 </td> <td style="text-align:right;"> 0.1923 </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> 2 </td> <td style="text-align:left;"> 4 </td> <td style="text-align:right;"> 1.802 </td> <td style="text-align:right;"> 1.5317 </td> <td style="text-align:right;"> 5 </td> <td style="text-align:left;"> ▇▃▁▅▁▃▁▆ </td> </tr> <tr> <td style="text-align:left;"> in_pair_desire_5R </td> <td style="text-align:left;"> Mein Partner hat mich ignoriert. </td> <td style="text-align:left;"> rating_button </td> <td style="text-align:left;"> 0,4,1 approval </td> <td style="text-align:left;"> haven_labelled </td> <td style="text-align:left;"> 4. 0: stimmt nicht,<br>3. 1,<br>2. 2,<br>1. 3,<br>0. 4: stimmt genau </td> <td style="text-align:left;"> 0 </td> <td style="text-align:left;"> s1_demo\)hetero_relationship & runif(1) < 0.3		77	rating_button_label_width150 blank_button	50403	0.1957	0	4	4	3.480	0.9883	5	▁▁▁▁▁▂▁▇

grooming_broad

4 grooming items aggregated by robust_rowmeans

Distribution

Distribution of values for grooming_broad

15844 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
grooming_broad	4 grooming items aggregated by robust_rowmeans	numeric	15844	0.7472	-2.5	0.011	3	0.0006	0.9233	▂▆▇▃▁

saw_partner

Distribution

Distribution of values for saw_partner

21862 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
saw_partner	numeric	21862	0.6511	0	1	1	0.6581	0.4744	▅▁▁▁▇	NA

last_saw_partner_date

Distribution

## 324  unique, categorical values, so not shown.

22810 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
last_saw_partner_date	Date	22810	0.636	324	2016-05-03	2016-10-02	2017-03-23	NA

days_since_seeing_partner

Distribution

Distribution of values for days_since_seeing_partner

22810 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
days_since_seeing_partner	numeric	22810	0.636	0	0	72	2.294	5.277	▇▁▁▁▁	NA

time_since_seeing_partner

Distribution

Distribution of values for time_since_seeing_partner

22810 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
time_since_seeing_partner	numeric	22810	0.636	1	1	8	2.073	2.144	▇▁▁▁▁	NA

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "Goettigen Ovulatory Cycle Diaries 2",
  "description": "A 70-day online diary study focusing on menstrual cycles, sexuality, mood, and behaviour\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "identifier": "https://doi.org/10.17605/OSF.IO/XXXX",
  "creator": "Ruben C. Arslan",
  "citation": "Arslan, R.C., Driebe, XXXX",
  "url": "https://rubenarslan.github.io/gocd2",
  "datePublished": "2020-06-02",
  "temporalCoverage": "2014-2015",
  "spatialCoverage": "German-speaking countries, online",
  "keywords": ["session", "short", "created_date", "created", "modified", "ended", "expired", "browser", "andere", "andere_uc", "anderen", "anderer", "days_done", "days_since_beginning", "days_since_last_entry", "never_skipped_more_than_2", "money_earned", "refer_time_period", "good_mood", "self_esteem", "relationship_satisfaction", "stressed", "irritable", "loneliness", "risk_taking", "illness_pain", "illness_pain_specific", "illness_pain_other", "partner_illness_pain", "partner_illness_pain_specific", "partner_illness_pain_other", "following_usual_routine", "everyday_specify", "travel", "travel_how", "sleep_amount", "sleep_quality", "sleep_fell_asleep_time", "sleep_awoke_time", "time_friends", "time_work_uni", "time_sports", "time_people", "time_family", "food_amount", "meat", "alcohol", "smoking", "grooming_1", "grooming_2", "grooming_time_spent", "vanity_1", "vanity_2", "vanity_3", "grooming_activities", "skin", "hair", "social_life_active", "social_life_saw_people", "social_life_thought_about", "social_life_free", "relationship_change", "relationship_change_specify", "night_spent_with_partner", "contact_partner", "saw_partner_last", "love_showed_to_partner", "love_shown_by_partner", "mate_retention1", "mate_retention2", "mate_retention3", "conflict_partner", "desirability", "high_libido", "is_single", "sexual_desire_for_whom", "sexual_initiation_self", "sexual_initiation_partner", "in_pair_desire_1", "in_pair_desire_2R", "in_pair_desire_3R", "in_pair_desire_4", "in_pair_went_out", "in_pair_desire_6", "in_pair_desire_7", "in_pair_desire_8", "in_pair_desire_9", "in_pair_desire_10", "in_pair_desire_11", "in_pair_desire_12", "in_pair_desire_13", "in_pair_desire_14", "in_pair_desire_5R", "extra_pair_desire_1", "extra_pair_desire_2R", "extra_pair_desire_3R", "extra_pair_desire_4", "extra_pair_went_out", "extra_pair_desire_6", "extra_pair_desire_7", "extra_pair_desire_8", "extra_pair_desire_9", "extra_pair_desire_10", "extra_pair_desire_11", "extra_pair_desire_12", "extra_pair_desire_13", "extra_pair_desire_14", "extra_pair_desire_5R", "extra_pair_desire_16", "sexual_desire_wants_desire", "sexual_desire_fulfill_sex_needs", "sexual_desire_fulfill_partner", "sexual_desire_for_activity", "last_had_sex", "sex_active", "no_sex_reason", "sex_acts", "sex_1_time", "sex_1_withwhom", "sex_1_activity", "sex_1_contraception", "sex_1_happy", "sex_1_enjoyed", "sex_1_partner_enjoyed", "sex_1_fantasy_partner", "sex_1_fantasy_actions", "sex_2_time", "sex_2_withwhom", "sex_2_activity", "sex_2_contraception", "sex_2_happy", "sex_2_enjoyed", "sex_2_partner_enjoyed", "sex_2_fantasy_partner", "sex_2_fantasy_actions", "menstrual_pain", "special_events_love_life", "menstruation_since_last_entry", "menstruation_today", "menstrual_onset", "menstrual_onset_date", "spotting", "answered_honestly_today", "dishonest_answers", "notes_to_us", "grooming", "vanity", "mate_retention", "in_pair_desire", "extra_pair_desire", "weekday", "weekend", "sleep_duration", "first_diary_day", "progesterone_mean", "progesterone_diff", "progesterone_log_mean", "progesterone_log_diff", "estradiol_mean", "estradiol_diff", "estradiol_log_mean", "estradiol_log_diff", "ibl_estradiol_mean", "ibl_estradiol_diff", "ibl_estradiol_log_mean", "ibl_estradiol_log_diff", "testosterone_mean", "testosterone_diff", "testosterone_log_mean", "testosterone_log_diff", "cortisol_mean", "cortisol_diff", "cortisol_log_mean", "cortisol_log_diff", "window_length", "date_of_ovulation_awareness", "diary_day_observation", "next_menstrual_onset", "last_menstrual_onset", "menstrual_onset_days_until", "menstrual_onset_days_since", "date_origin", "menstruation_labelled", "next_menstrual_onset_if_no_last", "day_number", "number_of_cycles", "cycle_nr", "cycle_length", "cycle_nr_fully_observed", "mean_cycle_length_diary", "median_cycle_length_diary", "next_menstrual_onset_inferred", "RCD_inferred", "luteal_BC", "follicular_FC", "day_lh_surge", "day_of_ovulation", "day_of_ovulation_inferred", "day_of_ovulation_forward_counted", "date_of_ovulation_BC", "date_of_ovulation_inferred", "date_of_ovulation_forward_counted", "date_of_ovulation_LH", "DRLH", "date_of_ovulation_awareness_nr", "fertile_awareness", "date_of_ovulation_avg_follicular", "date_of_ovulation_avg_luteal", "date_of_ovulation_avg_luteal_inferred", "FCD", "RCD", "DAL", "RCD_squished", "RCD_squished_rounded", "RCD_inferred_squished", "RCD_rel_to_ovulation", "RCD_fab", "conception_risk_lh", "fertile_lh", "prc_stirn_b", "prc_wcx_b", "fertile_narrow", "fertile_broad", "fertile_window", "premenstrual_phase", "prc_stirn_b_squished", "prc_wcx_b_squished", "fertile_narrow_squished", "fertile_broad_squished", "fertile_window_squished", "premenstrual_phase_squished", "prc_stirn_b_inferred_squished", "prc_wcx_b_inferred_squished", "fertile_narrow_inferred_squished", "fertile_broad_inferred_squished", "fertile_window_inferred_squished", "premenstrual_phase_inferred_squished", "prc_stirn_b_forward_counted", "prc_wcx_b_forward_counted", "fertile_narrow_forward_counted", "fertile_broad_forward_counted", "fertile_window_forward_counted", "premenstrual_phase_forward_counted", "prc_stirn_b_aware_luteal", "prc_wcx_b_aware_luteal", "fertile_narrow_aware_luteal", "fertile_broad_aware_luteal", "fertile_window_aware_luteal", "premenstrual_phase_aware_luteal", "prc_stirn_b_inferred", "prc_wcx_b_inferred", "fertile_narrow_inferred", "fertile_broad_inferred", "fertile_window_inferred", "premenstrual_phase_inferred", "fertile_fab", "premenstrual_phase_fab", "menstruation_imputed", "menstruation", "extra_pair_desire_and_behaviour", "extra_pair_interest", "in_pair_desire_and_behaviour", "in_pair_interest", "grooming_broad", "saw_partner", "last_saw_partner_date", "days_since_seeing_partner", "time_since_seeing_partner"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    },
    {
      "name": "created_date",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "browser",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "andere",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "andere_uc",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "anderen",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "anderer",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "days_done",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "days_since_beginning",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "days_since_last_entry",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "never_skipped_more_than_2",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "money_earned",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "refer_time_period",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "good_mood",
      "description": "Meine Stimmung war gut.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "self_esteem",
      "description": "Ich war zufrieden mit mir.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_satisfaction",
      "description": "Ich  war zufrieden mit meiner Beziehung.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "stressed",
      "description": "Ich war gestresst.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "irritable",
      "description": "Ich war leicht reizbar.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "loneliness",
      "description": "Ich war einsam.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "risk_taking",
      "description": "Ich  war risikobereit.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "illness_pain",
      "description": "Ich war krank/hatte Schmerzen.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "illness_pain_specific",
      "description": "Das hatte ich:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "headache. Kopfschmerzen,\nmigraine. Migräne,\nbladder_infection. Blasenentzündung,\ncold. Erkältung,\nflu. Grippe,\ngastrointestinal. Magen-Darm,\nback_pain. Rückenschmerzen,\nother. Andere",
      "maxValue": "other",
      "minValue": "back_pain",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "illness_pain_other",
      "description": "andere:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_illness_pain",
      "description": "Mein Partner war krank/hatte Schmerzen.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_illness_pain_specific",
      "description": "Das hatte er:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "headache. Kopfschmerzen,\nmigraine. Migräne,\nbladder_infection. Blasenentzündung,\ncold. Erkältung,\nflu. Grippe,\ngastrointestinal. Magen-Darm,\nback_pain. Rückenschmerzen,\nother. Andere",
      "maxValue": "other",
      "minValue": "back_pain",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "partner_illness_pain_other",
      "description": "andere:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "following_usual_routine",
      "description": "Ich bin meinem Alltag nachgegangen.",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "everyday_specify",
      "description": "Das war anders als sonst:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "travel",
      "description": "Ich bin gereist.",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "travel_how",
      "description": "So sah meine Reise aus:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "alone. alleine,\nwith_family. mit Familie,\nwith_friends. mit Freunden,\nwith_partner. `r ifelse(s1_demo$hetero_relationship, 'mit Partner', '')`,\njob_related. beruflich,\nvacation. Urlaub,\nvisit. Besuch,\nold_home. altes Zuhause",
      "maxValue": "with_partner",
      "minValue": "alone",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sleep_amount",
      "description": "So viel habe ich letzte Nacht geschlafen:",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sleep_quality",
      "description": "Mein Schlaf letzte Nacht war  gut.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sleep_fell_asleep_time",
      "@type": "propertyValue"
    },
    {
      "name": "sleep_awoke_time",
      "@type": "propertyValue"
    },
    {
      "name": "time_friends",
      "description": "Ich habe Zeit mit Freunden verbracht.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "time_work_uni",
      "description": "Ich habe Zeit mit Arbeiten/Uni verbracht.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "time_sports",
      "description": "Ich habe Sport getrieben.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "time_people",
      "description": "Ich haben Kontakt zu anderen Menschen gesucht.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "time_family",
      "description": "Ich habe Kontakt zu meiner Familie gesucht.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "food_amount",
      "description": "So viel habe ich gegessen:",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "meat",
      "description": "Ich habe Fleisch gegessen.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "alcohol",
      "description": "Ich habe Alkohol getrunken.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "smoking",
      "description": "Ich habe geraucht.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "grooming_1",
      "description": "Ich war aufgestyled.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "grooming_2",
      "description": "Ich habe mir Mühe mit meinem Outfit (Kleidung, Make-Up, ...) gegeben.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "grooming_time_spent",
      "description": "So viele Minuten habe ich insgesamt investiert, um mich ausgehfertig zu machen:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "vanity_1",
      "description": "Ich war mit meinem Aussehen zufrieden.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "vanity_2",
      "description": "Ich habe mich gerne im Spiegel angeschaut.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "vanity_3",
      "description": "Ich habe meinen Körper gerne angeschaut.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "grooming_activities",
      "description": "Heute hab ich mir die ...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "shaved_legs. <small>Beinhaare entfernt<\/small>,\nshaved_armpits. <small>Achselhaare entfernt<\/small>,\nshaved_bikini_zone. <small>Schamhaare entfernt<\/small>,\nplucked_eyebrows. <small>Augen-brauen gezupft<\/small>,\nmade_hair. <small>Haare frisiert<\/small>",
      "maxValue": "shaved_legs",
      "minValue": "made_hair",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "skin",
      "description": "Meine Haut war...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "super. super,\nas_always. wie immer,\nfattier. fettiger,\ndrier. trockener,\nmore_pimples. pickliger,\nwrinklier. faltiger,\nmore_sensitive. <small>empfind-licher<\/small>",
      "maxValue": "wrinklier",
      "minValue": "as_always",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hair",
      "description": "Meine Haare waren...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "super. super,\nas_always. wie immer,\nfattier. fettiger,\ndrier. trockener,\nfreshly_washed. <small>frisch gewaschen<\/small>,\nfreshly_coloured. <small>frisch <abbr title=\"oder getönt oder gebleicht\">gefärbt<\/abbr><\/small>,\nuntameable. <small>schwer zu bändigen<\/small>",
      "maxValue": "untameable",
      "minValue": "as_always",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "social_life_active",
      "description": "Ich war sozial aktiv.",
      "value": "was_alone. gar nicht (alleine gewesen),\nbarely. kaum (bspw. einkaufen gewesen),\njob_uni_related. nur arbeits-/universitätsbedingt (nicht mit Privatem verbunden),\nmet_one_purposefully. eine Person extra getroffen,\nmet_several_purposefully. mehrere Personen extra getroffen",
      "maxValue": "was_alone",
      "minValue": "barely",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "social_life_saw_people",
      "description": "Mit diesen Menschen hatte ich längeren sozialen Kontakt (mehr als eine Stunde).",
      "value": "1. `r paste(unique(stringr::str_trim(stringr::str_split(paste(na.omit(c(s3_daily$social_life_saw_people, s3_daily$social_life_thought_about)), collapse = \",\"), \",\")[[1]] )), collapse = \",\")`",
      "maxValue": "1",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "social_life_thought_about",
      "description": "An diese Menschen habe ich viel gedacht und hätte sie gerne gesehen.",
      "value": "1. `r paste(unique(stringr::str_trim(stringr::str_split(paste(na.omit(c(s3_daily$social_life_saw_people, s3_daily$social_life_thought_about)), collapse = \",\"), \",\")[[1]] )), collapse = \",\")`",
      "maxValue": "1",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "social_life_free",
      "description": "Das habe ich sozial unternommen:\n<small>optional<\/small>",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_change",
      "description": "In meiner  Beziehung hat sich etwas Wichtiges verändert:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "1. nein,\n2. Umzug,\n3. Auslandsaufenthalt,\n4. Änderung des Beziehungsstatus,\n5. etwas Anderes",
      "maxValue": "5",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "relationship_change_specify",
      "description": "Folgendes möchte ich dazu noch sagen:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "night_spent_with_partner",
      "description": "Ich habe die letzte Nacht mit meinem Partner verbracht.",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "contact_partner",
      "description": "Ich habe `r refer_time_period`...",
      "value": "1. ...fast die ganze Zeit mit meinem Partner verbracht.,\n2. ...viel Zeit mit meinem Partner verbracht.,\n3. ...mehrere Stunden mit meinem Partner verbracht.,\n4. ...meinen Partner nur kurz gesehen.,\n5. ...meinen Partner nicht gesehen, aber mehrfach mit ihm kommuniziert.,\n6. ...meinen Partner nicht gesehen, aber einmal mit ihm kommuniziert.,\n7. ...meinen Partner  weder gesehen, noch mit ihm kommuniziert.",
      "maxValue": 7,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "saw_partner_last",
      "description": "Ich habe meinen Partner vor heute zuletzt gesehen:",
      "value": "1. gestern,\n2. vorgestern,\n3. vor drei Tagen,\n4. vor 4 Tagen,\n5. vor 5 Tagen,\n6. vor 6 Tagen,\n7. vor ein bis zwei Wochen,\n8. vor mehr als zwei Wochen",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "love_showed_to_partner",
      "description": "Ich habe meinem Partner gezeigt, dass ich ihn liebe.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "love_shown_by_partner",
      "description": "Mein Partner hat mir gezeigt, dass er mich liebt.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mate_retention1",
      "description": "Mein Partner war anhänglich.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mate_retention2",
      "description": "Mein Partner war eifersüchtig.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "mate_retention3",
      "description": "Mein Partner war besitzergreifend.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "conflict_partner",
      "description": "Ich hatte Streit mit meinem Partner.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "desirability",
      "description": "Ich habe mich sexuell begehrenswert gefühlt.",
      "value": "0. 0: weniger als sonst,\n1. 1,\n2. 2,\n3. 3,\n4. 4: mehr als sonst",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "high_libido",
      "description": "Ich hatte eine hohe <abbr title=\"Lust, Geschlechtsverkehr zu haben/zu masturbieren/sexuell aktiv zu werden\">Libido<\/abbr>. ",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "is_single",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_desire_for_whom",
      "description": "Ich hatte Lust mit folgender Person sexuell aktiv zu werden:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "1. niemand bestimmtes,\n2. mit mir selbst,\n3. Bekannter/Freund,\n4. Bekannte/Freundin,\n5. Fremder,\n6. Fremde",
      "maxValue": "6",
      "minValue": "1",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_initiation_self",
      "description": "Ich habe sexuelle Handlungen mit meinem Partner initiiert.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_initiation_partner",
      "description": "Mein Partner hat sexuelle Handlungen mit mir initiiert.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_1",
      "description": "Ich habe an meinen Partner gedacht.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_2R",
      "description": "Ich hatte __keine__ Lust, Zeit mit meinem Partner zu verbringen.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_3R",
      "description": "Es war mir egal, ob mich mein Partner als attraktiv wahrnimmt.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_4",
      "description": "Mein Partner hat mit mir geflirtet.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_went_out",
      "description": "Ich bin __gemeinsam mit__  meinem Partner ausgegangen <small>(Party, Kneipe, Freunde treffen, ...).<\/small>",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_6",
      "description": "Ich habe mit meinem Partner geflirtet.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_7",
      "description": "Ich habe mich zu meinem Partner hingezogen gefühlt.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_8",
      "description": "Ich fand meinen Partner attraktiv.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_9",
      "description": "Mein Partner fand mich attraktiv.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_10",
      "description": "Ich habe mich von meinem Partner sexuell angezogen gefühlt.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_11",
      "description": "Ich hatte Lust, mit meinem Partner sexuell aktiv zu werden.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_12",
      "description": "Mein Partner schien Lust zu haben, mit mir sexuell aktiv zu werden.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_13",
      "description": "Ich hatte Fantasien über Zärtlichkeiten mit meinem Partner.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_14",
      "description": "Ich hatte Fantasien über Sex mit meinem Partner.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_5R",
      "description": "Mein Partner hat mich ignoriert.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_1",
      "description": "Ich habe an einen `r anderen` Mann gedacht.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_2R",
      "description": "Ich hatte __keine__ Lust, Zeit mit `r anderen` Männern zu verbringen.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_3R",
      "description": "Es war mir egal, ob mich `r andere` Männer als attraktiv wahrnehmen.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_4",
      "description": "Mich haben  `r andere` Männer angeflirtet.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_went_out",
      "description": "Ich bin `r ifelse(s1_demo$hetero_relationship, '__ohne__ meinen Partner', '')` ausgegangen <small>(Party, Kneipe, Freunde treffen, ...).<\/small>",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_6",
      "description": "Ich habe mit `r anderen` Männern geflirtet.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_7",
      "description": "Ich habe mich zu `r anderen` Männern hingezogen gefühlt.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_8",
      "description": "Mir sind `r andere` attraktive Männer in meiner Umgebung aufgefallen.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_9",
      "description": "`r andere_uc` Männer fanden mich attraktiv.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_10",
      "description": "Ich habe mich von einem `r anderen` Mann sexuell angezogen gefühlt.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_11",
      "description": "Ich hatte Lust mit einem `r anderen` Mann sexuell aktiv zu werden.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_12",
      "description": "Ein `r anderer` Mann schien Lust zu haben, mit mir sexuell aktiv zu werden.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_13",
      "description": "Ich hatte Fantasien über Zärtlichkeiten mit einem `r anderen` Mann.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_14",
      "description": "Ich hatte Fantasien über Sex mit einem `r anderen` Mann.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_5R",
      "description": "`r andere_uc` Männer haben mich ignoriert.",
      "value": "4. 0: stimmt nicht,\n3. 1,\n2. 2,\n1. 3,\n0. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_16",
      "description": "Ich habe mir Gedanken über `r andere` potentielle Partner gemacht.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_desire_wants_desire",
      "description": "Ich wollte begehrt werden.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_desire_fulfill_sex_needs",
      "description": "Ich wollte meine eigenen sexuellen Bedürfnisse erfüllen.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_desire_fulfill_partner",
      "description": "Ich wollte, dass mein Partner sich geliebt/begehrenswert fühlt.",
      "value": "0. 0: stimmt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: stimmt genau",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_desire_for_activity",
      "description": "Ich hatte auf folgende Art von sexueller Aktivität Lust:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "kissing. Küssen,\ncuddling. Kuscheln etc.,\nphone_skype_sex. Telefonsex/Webcamsex,\nsex. Geschlechtsverkehr (penetrativ),\nmasturbation. Selbstbefriedigung,\nmasturbated_by_partner. Partner mit Hand stimulieren,\nmasturbated_partner. von Partner mit Hand stimuliert werden,\nfellatio. Partner mit Mund stimulieren,\ncunnilingus. von Partner mit Mund stimuliert werden,\nanal_sex. Analverkehr,\ntoys. Spielzeuge (Vibrator; ...),\nbdsm_sub. BDSM-Elemente; ich submissiv (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nbdsm_dom. BDSM-Elemente; ich dominant (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nnothing_particular. nichts bestimmtes",
      "maxValue": "toys",
      "minValue": "anal_sex",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "last_had_sex",
      "description": "Ich hatte vor heute zuletzt mit meinem Partner Sex:",
      "value": "1. gestern,\n2. vorgestern,\n3. vor drei Tagen,\n4. vor 4 Tagen,\n5. vor 5 Tagen,\n6. vor 6 Tagen,\n7. vor ein bis zwei Wochen,\n8. vor mehr als zwei Wochen",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_active",
      "description": "Ich war `r refer_time_period` sexuell aktiv (auch Selbstbefriedigung, Zärtlichkeiten)...",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "no_sex_reason",
      "description": "Deshalb war ich nicht sexuell aktiv...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "just_didnt_happen. Es kam nicht dazu.,\nno_desire. Ich hatte keine Lust.,\nno_time. Ich hatte keine Zeit.,\nhad_no_partner. `r ifelse(s1_demo$hetero_relationship, '', 'Ich hatte keinen Partner.')`,\ndidnt_see_partner. `r ifelse(s1_demo$hetero_relationship, 'Nicht genug Zeit mit Partner.', '')`,\npartner_didnt_want_to. `r ifelse(s1_demo$hetero_relationship, 'Mein Partner wollte nicht.', '')`,\npartner_couldnt. `r ifelse(s1_demo$hetero_relationship, 'Mein Partner konnte nicht (Zeit, Krankheit, ...).', '')`,\nno_privacy. Ich hatte nicht genug Privatsphäre.,\nno_contraception. Ich hatte kein Verhütungsmittel.,\ntired. Ich war müde.,\nfelt_gross. Ich habe mich eklig gefühlt. ,\nfelt_unattractive. Ich habe mich unattraktiv gefühlt.,\nhad_pain. Mir hat etwas wehgetan.,\nsick. Ich war krank.,\nbladder_yeast_infection. Ich hatte eine Blasenentzündung oder Hefepilz.,\nmenstruation. Ich hatte meine Tage.",
      "maxValue": "tired",
      "minValue": "bladder_yeast_infection",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_acts",
      "description": "Wie oft?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_time",
      "description": "Wann?",
      "value": "t0_yesterday_evening. gestern Abend,\nt1_before_falling_asleep. gestern vor dem Einschlafen,\nt2_night_time. gestern Nacht,\nt3_after_waking_up. nach dem Aufwachen,\nt4_morning. morgens,\nt5_during_day. tagsüber,\nt6_evening. heute Abend",
      "maxValue": "t6_evening",
      "minValue": "t0_yesterday_evening",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_withwhom",
      "description": "Mit wem?\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "solo. alleine,\nwith_partner. `r ifelse(s1_demo$hetero_relationship == 1, 'mit Partner', '')`,\nwith_partner_tele. `r ifelse(s1_demo$hetero_relationship == 1, 'Partner via Telefon/Webcam', '')`,\nother_female. andere weibliche Person,\nother_male. andere männliche Person",
      "maxValue": "with_partner_tele",
      "minValue": "other_female",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_activity",
      "description": "Es handelte sich um folgende sexuelle Aktivität/en:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "kissing. Küssen,\ncuddling. Kuscheln etc.,\nphone_skype_sex. Telefonsex/Webcamsex,\nsex. Geschlechtsverkehr (penetrativ),\nmasturbation. Selbstbefriedigung,\nmasturbated_by_partner. von Partner mit Hand stimuliert,\nmasturbated_partner. habe Partner mit Hand stimuliert,\nfellatio. habe Partner mit Mund stimuliert,\ncunnilingus. von Partner mit Mund stimuliert,\nanal_sex. Analverkehr,\ntoys. Spielzeuge (Vibrator; ...),\nbdsm_sub. BDSM-Elemente; ich submissiv (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nbdsm_dom. BDSM-Elemente; ich dominant (Handschellen/Fesseln; Augenbinden; Spanking; etc.)",
      "maxValue": "toys",
      "minValue": "anal_sex",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_contraception",
      "description": "Ich habe folgendermaßen verhütet:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "long_term. langfristige Verhütung (Pille, Pessar, Ring, etc.),\ncondom. Kondom,\ncoitus_interruptus. Koitus interruptus (Rausziehen),\ndiaphragm. Diaphragma,\nspermicide. Spermizid,\ncounted_days. wusste, dass ich heute nicht fruchtbar bin,\nnot_necessary. nicht notwendig (bspw. bei Selbstbefriedigung),\ndid_not_want. wollte heute nicht verhüten,\nrisked_it. hab's riskiert",
      "maxValue": "spermicide",
      "minValue": "coitus_interruptus",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_happy",
      "description": "Der sexuelle Akt hat mich glücklich gemacht.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_enjoyed",
      "description": "Ich war sexuell befriedigt.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_partner_enjoyed",
      "description": "Mein Partner war sexuell befriedigt.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_fantasy_partner",
      "description": "Gedacht habe ich dabei an ...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "partner. `r ifelse(s1_demo$hetero_relationship, 'meinen Partner', '')`,\nanother_woman_known. eine andere Frau, die ich kenne,\nanother_man_known. einen `r anderen` Mann, den ich kenne,\nanother_woman_media. <small>eine andere Frau (aus Buch, Film, Medien, ...)<\/small>,\nanother_man_media. <small>einen `r anderen` Mann (aus Buch, Film, Medien, ...)<\/small>,\nman_pornography. <small>Mann aus erotischen Medien<\/small>,\nwoman_pornography. <small>Frau aus erotischen Medien<\/small>,\nnobody_in_particular. niemand bestimmtes,\nnot_concrete. nichts konkretes",
      "maxValue": "woman_pornography",
      "minValue": "another_man_known",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_1_fantasy_actions",
      "description": "Ich habe dabei an folgende Handlunge(n) gedacht...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "kissing. Küssen,\ncuddling. Kuscheln etc.,\nphone_skype_sex. Telefonsex/Webcamsex,\nsex. Geschlechtsverkehr (penetrativ),\nmasturbation. Selbstbefriedigung,\nmasturbated_by_partner. Partner mit Hand stimulieren,\nmasturbated_partner. von Partner mit Hand stimuliert werden,\nfellatio. Partner mit Mund stimulieren,\ncunnilingus. von Partner mit Mund stimuliert werden,\nanal_sex. Analverkehr,\ntoys. Spielzeuge (Vibrator; ...),\nbdsm_sub. BDSM-Elemente; ich submissiv (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nbdsm_dom. BDSM-Elemente; ich dominant (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nnothing_particular. nichts bestimmtes",
      "maxValue": "toys",
      "minValue": "anal_sex",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_time",
      "description": "Wann?",
      "value": "t0_yesterday_evening. gestern Abend,\nt1_before_falling_asleep. gestern vor dem Einschlafen,\nt2_night_time. gestern Nacht,\nt3_after_waking_up. nach dem Aufwachen,\nt4_morning. morgens,\nt5_during_day. tagsüber,\nt6_evening. heute Abend",
      "maxValue": "t6_evening",
      "minValue": "t0_yesterday_evening",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_withwhom",
      "description": "Mit wem?\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "solo. alleine,\nwith_partner. `r ifelse(s1_demo$hetero_relationship == 1, 'mit Partner', '')`,\nwith_partner_tele. `r ifelse(s1_demo$hetero_relationship == 1, 'Partner via Telefon/Webcam', '')`,\nother_female. andere weibliche Person,\nother_male. andere männliche Person",
      "maxValue": "with_partner_tele",
      "minValue": "other_female",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_activity",
      "description": "Es handelte sich um folgende sexuelle Aktivität/en:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "kissing. Küssen,\ncuddling. Kuscheln etc.,\nphone_skype_sex. Telefonsex/Webcamsex,\nsex. Geschlechtsverkehr (penetrativ),\nmasturbation. Selbstbefriedigung,\nmasturbated_by_partner. von Partner mit Hand stimuliert,\nmasturbated_partner. habe Partner mit Hand stimuliert,\nfellatio. habe Partner mit Mund stimuliert,\ncunnilingus. von Partner mit Mund stimuliert,\nanal_sex. Analverkehr,\ntoys. Spielzeuge (Vibrator; ...),\nbdsm_sub. BDSM-Elemente; ich submissiv (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nbdsm_dom. BDSM-Elemente; ich dominant (Handschellen/Fesseln; Augenbinden; Spanking; etc.)",
      "maxValue": "toys",
      "minValue": "anal_sex",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_contraception",
      "description": "Ich habe folgendermaßen verhütet:\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "long_term. langfristige Verhütung (Pille, Pessar, Ring, etc.),\ncondom. Kondom,\ncoitus_interruptus. Koitus interruptus (Rausziehen),\ndiaphragm. Diaphragma,\nspermicide. Spermizid,\ncounted_days. wusste, dass ich heute nicht fruchtbar bin,\nnot_necessary. nicht notwendig (bspw. bei Selbstbefriedigung),\ndid_not_want. wollte heute nicht verhüten,\nrisked_it. hab's riskiert",
      "maxValue": "spermicide",
      "minValue": "coitus_interruptus",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_happy",
      "description": "Der sexuelle Akt hat mich glücklich gemacht.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_enjoyed",
      "description": "Ich war sexuell befriedigt.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_partner_enjoyed",
      "description": "Mein Partner war sexuell befriedigt.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_fantasy_partner",
      "description": "Gedacht habe ich dabei an ...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "partner. `r ifelse(s1_demo$hetero_relationship, 'meinen Partner', '')`,\nanother_woman_known. eine andere Frau, die ich kenne,\nanother_man_known. einen `r anderen` Mann, den ich kenne,\nanother_woman_media. <small>eine andere Frau (aus Buch, Film, Medien, ...)<\/small>,\nanother_man_media. <small>einen `r anderen` Mann (aus Buch, Film, Medien, ...)<\/small>,\nman_pornography. <small>Mann aus erotischen Medien<\/small>,\nwoman_pornography. <small>Frau aus erotischen Medien<\/small>,\nnobody_in_particular. niemand bestimmtes,\nnot_concrete. nichts konkretes",
      "maxValue": "woman_pornography",
      "minValue": "another_man_known",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sex_2_fantasy_actions",
      "description": "Ich habe dabei an folgende Handlunge(n) gedacht...\n<small>(Mehrfachnennungen möglich)<\/small>",
      "value": "kissing. Küssen,\ncuddling. Kuscheln etc.,\nphone_skype_sex. Telefonsex/Webcamsex,\nsex. Geschlechtsverkehr (penetrativ),\nmasturbation. Selbstbefriedigung,\nmasturbated_by_partner. Partner mit Hand stimulieren,\nmasturbated_partner. von Partner mit Hand stimuliert werden,\nfellatio. Partner mit Mund stimulieren,\ncunnilingus. von Partner mit Mund stimuliert werden,\nanal_sex. Analverkehr,\ntoys. Spielzeuge (Vibrator; ...),\nbdsm_sub. BDSM-Elemente; ich submissiv (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nbdsm_dom. BDSM-Elemente; ich dominant (Handschellen/Fesseln; Augenbinden; Spanking; etc.),\nnothing_particular. nichts bestimmtes",
      "maxValue": "toys",
      "minValue": "anal_sex",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_pain",
      "description": "Ich hatte <abbr title=\"auch prämenstruelle\">menstruationsbedingte<\/abbr> Schmerzen.",
      "value": "0. 0: überhaupt nicht,\n1. 1,\n2. 2,\n3. 3,\n4. 4: sehr viel",
      "maxValue": 4,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "special_events_love_life",
      "description": "Es gab besondere nennenswerte Ereignisse hinsichtlich meines Liebeslebens:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_since_last_entry",
      "description": "Ich hatte `r ifelse(days_since_last_entry > 3, \"seit meinem letzten Tagebucheintrag\", \"in den letzten 3 Tagen\")` menstruelle Blutungen.\n<small>(Periode, nicht Zwischenblutung)<\/small>",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_today",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_onset",
      "description": "Heute war der erste Tag meiner menstruellen Blutung...",
      "value": "1. ja ,\n2. nein (gestern),\n3. nein (vorgestern),\n4. nein (vor 3 Tagen),\n5. nein (vor 4 Tagen),\n6. nein (vor 5 Tagen),\n7. nein (vor 6 Tagen),\n8. nein (Beginn liegt noch länger zurück)",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_onset_date",
      "description": "Datum der ersten menstruellen Blutung",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "spotting",
      "description": "Ich hatte heute eine Zwischenblutung.",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "answered_honestly_today",
      "description": "__Ich habe alles ehrlich ausgefüllt, und nicht zufällig auf Antworten geklickt.__\n<small>Ihnen entsteht durch Ehrlichkeit hier kein Nachteil (d. h.  wir ziehen es nicht von Ihrem Guthaben ab), aber erlauben uns so, invalide Daten von unserer Untersuchung auszuschließen.<\/small>",
      "value": "0. Nein,\n1. Ja",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "dishonest_answers",
      "description": "Wollen Sie uns genauer sagen, ob Sie alle Fragen falsch beantwortet haben (bspw. zufällig durchgeklickt) oder nur manche (bspw. zur Wahrung Ihrer Intimsphäre)?\n<small>optional<\/small>",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "notes_to_us",
      "description": "Ich möchte dem Studienteam folgendes mitteilen:\n<small>optional<\/small>",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "grooming",
      "description": "Self-grooming (broad)",
      "@type": "propertyValue"
    },
    {
      "name": "vanity",
      "description": "Satisfied with looks",
      "@type": "propertyValue"
    },
    {
      "name": "mate_retention",
      "description": "Partner mate retention",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire",
      "description": "In-pair desire",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire",
      "description": "Extra-pair desire",
      "@type": "propertyValue"
    },
    {
      "name": "weekday",
      "value": "1. Monday,\n2. Tuesday,\n3. Wednesday,\n4. Thursday,\n5. Friday,\n6. Saturday,\n7. Sunday",
      "@type": "propertyValue"
    },
    {
      "name": "weekend",
      "@type": "propertyValue"
    },
    {
      "name": "sleep_duration",
      "@type": "propertyValue"
    },
    {
      "name": "first_diary_day",
      "@type": "propertyValue"
    },
    {
      "name": "progesterone_mean",
      "@type": "propertyValue"
    },
    {
      "name": "progesterone_diff",
      "@type": "propertyValue"
    },
    {
      "name": "progesterone_log_mean",
      "@type": "propertyValue"
    },
    {
      "name": "progesterone_log_diff",
      "@type": "propertyValue"
    },
    {
      "name": "estradiol_mean",
      "@type": "propertyValue"
    },
    {
      "name": "estradiol_diff",
      "@type": "propertyValue"
    },
    {
      "name": "estradiol_log_mean",
      "@type": "propertyValue"
    },
    {
      "name": "estradiol_log_diff",
      "@type": "propertyValue"
    },
    {
      "name": "ibl_estradiol_mean",
      "@type": "propertyValue"
    },
    {
      "name": "ibl_estradiol_diff",
      "@type": "propertyValue"
    },
    {
      "name": "ibl_estradiol_log_mean",
      "@type": "propertyValue"
    },
    {
      "name": "ibl_estradiol_log_diff",
      "@type": "propertyValue"
    },
    {
      "name": "testosterone_mean",
      "@type": "propertyValue"
    },
    {
      "name": "testosterone_diff",
      "@type": "propertyValue"
    },
    {
      "name": "testosterone_log_mean",
      "@type": "propertyValue"
    },
    {
      "name": "testosterone_log_diff",
      "@type": "propertyValue"
    },
    {
      "name": "cortisol_mean",
      "@type": "propertyValue"
    },
    {
      "name": "cortisol_diff",
      "@type": "propertyValue"
    },
    {
      "name": "cortisol_log_mean",
      "@type": "propertyValue"
    },
    {
      "name": "cortisol_log_diff",
      "@type": "propertyValue"
    },
    {
      "name": "window_length",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_awareness",
      "@type": "propertyValue"
    },
    {
      "name": "diary_day_observation",
      "@type": "propertyValue"
    },
    {
      "name": "next_menstrual_onset",
      "@type": "propertyValue"
    },
    {
      "name": "last_menstrual_onset",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_onset_days_until",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_onset_days_since",
      "@type": "propertyValue"
    },
    {
      "name": "date_origin",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_labelled",
      "value": "1. yes,\n2. probably,\n3. no",
      "@type": "propertyValue"
    },
    {
      "name": "next_menstrual_onset_if_no_last",
      "@type": "propertyValue"
    },
    {
      "name": "day_number",
      "@type": "propertyValue"
    },
    {
      "name": "number_of_cycles",
      "@type": "propertyValue"
    },
    {
      "name": "cycle_nr",
      "@type": "propertyValue"
    },
    {
      "name": "cycle_length",
      "@type": "propertyValue"
    },
    {
      "name": "cycle_nr_fully_observed",
      "@type": "propertyValue"
    },
    {
      "name": "mean_cycle_length_diary",
      "@type": "propertyValue"
    },
    {
      "name": "median_cycle_length_diary",
      "@type": "propertyValue"
    },
    {
      "name": "next_menstrual_onset_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "luteal_BC",
      "@type": "propertyValue"
    },
    {
      "name": "follicular_FC",
      "@type": "propertyValue"
    },
    {
      "name": "day_lh_surge",
      "@type": "propertyValue"
    },
    {
      "name": "day_of_ovulation",
      "@type": "propertyValue"
    },
    {
      "name": "day_of_ovulation_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "day_of_ovulation_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_BC",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_LH",
      "@type": "propertyValue"
    },
    {
      "name": "DRLH",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_awareness_nr",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_awareness",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_avg_follicular",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_avg_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "date_of_ovulation_avg_luteal_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "FCD",
      "@type": "propertyValue"
    },
    {
      "name": "RCD",
      "@type": "propertyValue"
    },
    {
      "name": "DAL",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_squished",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_squished_rounded",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_rel_to_ovulation",
      "@type": "propertyValue"
    },
    {
      "name": "RCD_fab",
      "@type": "propertyValue"
    },
    {
      "name": "conception_risk_lh",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_lh",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b_squished",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window_squished",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_squished",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window_inferred_squished",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_inferred_squished",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window_forward_counted",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_forward_counted",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b_aware_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b_aware_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow_aware_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad_aware_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window_aware_luteal",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_aware_luteal",
      "@type": "propertyValue"
    },
    {
      "name": "prc_stirn_b_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "prc_wcx_b_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_narrow_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_broad_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_window_inferred",
      "value": "1. infertile,\n2. broad,\n3. narrow",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_inferred",
      "@type": "propertyValue"
    },
    {
      "name": "fertile_fab",
      "description": "Est. fertile window prob. (BC+i)",
      "@type": "propertyValue"
    },
    {
      "name": "premenstrual_phase_fab",
      "description": "Est. premenstrual phase (BC+i)",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation_imputed",
      "@type": "propertyValue"
    },
    {
      "name": "menstruation",
      "description": "Est. menstruation",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_desire_and_behaviour",
      "description": "Extra-pair desire and behaviour",
      "@type": "propertyValue"
    },
    {
      "name": "extra_pair_interest",
      "description": "Extra-pair interest",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_desire_and_behaviour",
      "description": "In-pair desire and behaviour",
      "@type": "propertyValue"
    },
    {
      "name": "in_pair_interest",
      "description": "In-pair interest",
      "@type": "propertyValue"
    },
    {
      "name": "grooming_broad",
      "description": "4 grooming items aggregated by robust_rowmeans",
      "@type": "propertyValue"
    },
    {
      "name": "saw_partner",
      "@type": "propertyValue"
    },
    {
      "name": "last_saw_partner_date",
      "@type": "propertyValue"
    },
    {
      "name": "days_since_seeing_partner",
      "@type": "propertyValue"
    },
    {
      "name": "time_since_seeing_partner",
      "@type": "propertyValue"
    }
  ]
}`

Time spent

Single participants answered questions about who they spent time with and/or thought about during the diary. We asked them questions about commonly mentioned names after the end of the diary.

Metadata

Description

Dataset name: s4_timespent

The dataset has N=2337 rows and 30 columns. 0 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
created
modified
ended
expired
person_nr
person
person_remember
person_sex
person_sex_other
person_age
person_relationship_status
person_relationship_to_anchor
person_kinship
person_romantic_experience
person_height
person_weight
person_attractiveness_short_term
person_attractiveness_long_term
person_attractive_body
person_kindness
person_education
person_extraversion
person_dominance
person_strength
person_financial
person_faithful
person_funny
person_notes
short

Survey overview

2331 completed rows, 2333 who entered any information, 4 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 2337 rows including unfinished and expired rows.

There were 355 unique participants, of which 349 finished filling out at least one survey.

This survey was repeated many times, on average 6.58 times per user.

Number of sessions

The first session started on 2016-07-12 17:21:47, the last session on 2017-04-13 13:39:40.

Starting date times

People took on average 225.86 minutes (median 0.78) to answer the survey.

Duration people took for answering the survey

#Variables

person_nr

Distribution

Distribution of values for person_nr

0 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
person_nr		calculate	character	0		nrow(s4_timespent)	1	0	1	10	0	1	2	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	person_nr		0		nrow(s4_timespent)	1

Value labels

Response choices
name	value

person

Distribution

Distribution of values for person

92 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
person		calculate	character	0		person_names = plyr::count(stringr::str_trim(stringr::str_split(paste(na.omit(c(s3_daily$social_life_saw_people, s3_daily$social_life_thought_about)), collapse = “,”), “,”)[[1]])) person_names = person_names[order(person_names$freq), ] tail(person_names[person_names$freq > 3, ‘x’], 10)person_nr	2	92	0.9606	1391	0	1	52	0

Item

Item options
type	name	label	optional	showif	value	item_order
calculate	person		0		person_names = plyr::count(stringr::str_trim(stringr::str_split(paste(na.omit(c(s3_daily$social_life_saw_people, s3_daily$social_life_thought_about)), collapse = “,”), “,”)[[1]])) person_names = person_names[order(person_names$freq), ] tail(person_names[person_names$freq > 3, ‘x’], 10)person_nr	2

Value labels

Response choices
name	value

person_remember

Ich weiß noch, wen ich mit “r person” im Tagebuch meinte.

Distribution

Distribution of values for person_remember

6 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		person_remember	Ich weiß noch, wen ich mit “`r person`” im Tagebuch meinte.	0			102

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

person_sex

Geschlecht von r person:

Distribution

Distribution of values for person_sex

216 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_sex

Item

Item options
type	name	label	optional	showif	value	item_order
mc	person_sex	Geschlecht von `r person`:	0	person_remember == 1 //js_only		103

Value labels

Response choices
name	value
weiblich	1
männlich	2
andere	3
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_sex_other

Andere:

Distribution

Distribution of values for person_sex_other

2174 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
person_sex_other	Andere:	text	character	0	person_sex == 3 //js_only		104	2174	0.0697	90	0	1	117	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	person_sex_other	Andere:	0	person_sex == 3 //js_only		104

Value labels

Response choices
name	value

person_age

Alter von r person:

Distribution

Distribution of values for person_age

216 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_age

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,110,1	person_age	Alter von `r person`:	0	person_remember == 1 //js_only		105

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_relationship_status

Beziehungsstatus von r person:

Distribution

Distribution of values for person_relationship_status

216 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		person_relationship_status	Beziehungsstatus von `r person`:	0	mc_vertical	person_remember == 1 //js_only		106

Value labels

Response choices
name	value
1	single
2	partnered
3	engaged
4	married
5	unclear_status
6	dont_know

person_relationship_to_anchor

Wie stehen Sie zu r person?

Distribution

Distribution of values for person_relationship_to_anchor

216 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc		person_relationship_to_anchor	Wie stehen Sie zu `r person`?	0	mc_vertical	person_remember == 1 //js_only		107

Value labels

Response choices
name	value
1	loose_acquaintance
2	acquaintance
3	friend
4	biological_relative
5	nonbiological_relative
6	romantic_short_term_relationship
7	romantic_long_term_relationship

person_kinship

Wie sind Sie mit r person verwandt?

Distribution

Distribution of values for person_kinship

1896 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
select_or_add_one		person_kinship	Wie sind Sie mit `r person` verwandt?	0	person_remember == 1 && (person_relationship_to_anchor == “biological_relative” \|\| person_relationship_to_anchor == “nonbiological_relative”) //js_only		108

Value labels

Response choices
name	value
1	mother
2	father
3	brother
4	sister
5	aunt
6	uncle
7	cousin
8	daughter
9	son
10	nephew
11	niece

person_romantic_experience

Hatten Sie und r person je eine romantische oder sexuelle Erfahrung miteinander? Wählen Sie bitte die “höchste” zutreffende Antwort.

Distribution

Distribution of values for person_romantic_experience

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		person_romantic_experience	Hatten Sie und `r person` je eine romantische oder sexuelle Erfahrung miteinander? <small>Wählen Sie bitte die “höchste” zutreffende Antwort.</small>	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		109

Value labels

Response choices
name	value
1	none
2	flirt
3	date
4	make_out
5	sex

person_height

Was ist die ungefähre Körpergröße von r person in cm (ohne Schuhe)?

Distribution

Distribution of values for person_height

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_height

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	80,230	person_height	Was ist die ungefähre Körpergröße von `r person` in cm (ohne Schuhe)?	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		110

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_weight

Was ist das ungefähre Gewicht von r person in kg (ohne Kleidung)?

Distribution

Distribution of values for person_weight

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_weight

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	40,200	person_weight	Was ist das ungefähre Gewicht von `r person` in kg (ohne Kleidung)?	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		111

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_attractiveness_short_term

Ich finde r person attraktiv für einen One-Night-Stand oder eine kurze sexuelle Affäre mit mir.

Distribution

Distribution of values for person_attractiveness_short_term

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_attractiveness_short_term

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_attractiveness_short_term	Ich finde `r person` attraktiv für einen One-Night-Stand oder eine kurze sexuelle Affäre mit mir.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_attractiveness_long_term

Ich finde r person attraktiv für eine langfristige Beziehung (feste Partnerschaft, Ehe, …) mit mir.

Distribution

Distribution of values for person_attractiveness_long_term

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_attractiveness_long_term

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_attractiveness_long_term	Ich finde `r person` attraktiv für eine langfristige Beziehung (feste Partnerschaft, Ehe, …) mit mir.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_attractive_body

r person hat einen attraktiven Körper und Gesicht.

Distribution

Distribution of values for person_attractive_body

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_attractive_body

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_attractive_body	`r person` hat einen attraktiven Körper und Gesicht.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_kindness

r person ist warmherzig, ein guter Mensch.

Distribution

Distribution of values for person_kindness

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_kindness

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_kindness	`r person` ist warmherzig, ein guter Mensch.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_education

r person ist gebildet, war gut in der Schule/Universität.

Distribution

Distribution of values for person_education

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_education

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_education	`r person` ist gebildet, war gut in der Schule/Universität.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_extraversion

r person ist gesellig, gerne unter Menschen.

Distribution

Distribution of values for person_extraversion

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_extraversion

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_extraversion	`r person` ist gesellig, gerne unter Menschen.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_dominance

r person ist dominant.

Distribution

Distribution of values for person_dominance

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_dominance

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_dominance	`r person` ist dominant.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_strength

r person ist körperlich stärker als viele andere Männer.

Distribution

Distribution of values for person_strength

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_strength

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_strength	`r person` ist körperlich stärker als viele andere Männer.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_financial

r person verdient gut oder wird einmal gut verdienen.

Distribution

Distribution of values for person_financial

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_financial

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_financial	`r person` verdient gut oder wird einmal gut verdienen.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_faithful

r person wäre in einer Beziehung treu.

Distribution

Distribution of values for person_faithful

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_faithful

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_faithful	`r person` wäre in einer Beziehung treu.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_funny

r person ist lustig, unterhaltsam.

Distribution

Distribution of values for person_funny

1673 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for person_funny

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	1,5 agree	person_funny	`r person` ist lustig, unterhaltsam.	0	person_sex == 2 & person_relationship_to_anchor != “biological_relative” //js_only		121

Value labels

Response choices
name	value
1: trifft überhaupt nicht zu	1
2	2
3	3
4	4
5: trifft voll und ganz zu	5
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

person_notes

Wir haben versucht, es kurz zu halten. Haben Sie noch Anmerkungen zu r person, die durch unsere Fragen nicht oder nicht gut erfasst wurden?

Distribution

Distribution of values for person_notes

1734 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
person_notes	Wir haben versucht, es kurz zu halten. Haben Sie noch Anmerkungen zu `r person`, die durch unsere Fragen nicht oder nicht gut erfasst wurden?	textarea	character	1	person_remember == 1 //js_only		149	1734	0.258	559	0	2	678	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	person_notes	Wir haben versucht, es kurz zu halten. Haben Sie noch Anmerkungen zu `r person`, die durch unsere Fragen nicht oder nicht gut erfasst wurden?	1	person_remember == 1 //js_only		149

Value labels

Response choices
name	value

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	355	0	7	7	0	NA

Missingness report

## # A tibble: 13 x 29
##    description modified ended person_remember person person_sex person_age person_relation… person_relation…
##    <chr>          <dbl> <dbl>           <dbl>  <dbl>      <dbl>      <dbl>            <dbl>            <dbl>
##  1 Missing va…        4     6               6     92        216        216              216              216
##  2 Missing va…        1     1               1      1          1          1                1                1
##  3 Missing va…        1     1               1      1          1          1                1                1
##  4 Missing va…        1     1               1      1          1          1                1                1
##  5 Missing va…        1     1               1      1          1          1                1                1
##  6 Missing va…        1     1               1      1          1          1                1                1
##  7 Missing va…        1     1               1      1          0          0                0                0
##  8 Missing va…        1     1               1      0          0          0                0                0
##  9 Missing va…        1     1               1      1          1          1                1                1
## 10 Missing va…        1     1               1      1          1          1                1                1
## 11 Missing va…        1     1               1      1          1          1                1                1
## 12 Missing va…        1     1               1      1          1          1                1                1
## 13 10 other, …        9     8               8      6          7          7                7                7
## # … with 20 more variables: person_romantic_experience <dbl>, person_height <dbl>, person_weight <dbl>,
## #   person_attractiveness_short_term <dbl>, person_attractiveness_long_term <dbl>,
## #   person_attractive_body <dbl>, person_kindness <dbl>, person_education <dbl>, person_extraversion <dbl>,
## #   person_dominance <dbl>, person_strength <dbl>, person_financial <dbl>, person_faithful <dbl>,
## #   person_funny <dbl>, person_notes <dbl>, person_kinship <dbl>, person_sex_other <dbl>, expired <dbl>,
## #   var_miss <dbl>, n_miss <dbl>

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "s4_timespent",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=2337 rows and 30 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "created", "modified", "ended", "expired", "person_nr", "person", "person_remember", "person_sex", "person_sex_other", "person_age", "person_relationship_status", "person_relationship_to_anchor", "person_kinship", "person_romantic_experience", "person_height", "person_weight", "person_attractiveness_short_term", "person_attractiveness_long_term", "person_attractive_body", "person_kindness", "person_education", "person_extraversion", "person_dominance", "person_strength", "person_financial", "person_faithful", "person_funny", "person_notes", "short"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "person_nr",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person",
      "description": "",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_remember",
      "description": "Ich weiß noch, wen ich mit \"__`r person`__\" im Tagebuch meinte.",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_sex",
      "description": "Geschlecht von __`r person`__:",
      "value": "1. weiblich,\n2. männlich,\n3. andere,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 3,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_sex_other",
      "description": "Andere:",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_age",
      "description": "Alter von __`r person`__:",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_relationship_status",
      "description": "Beziehungsstatus von __`r person`__:",
      "value": "single. single,\npartnered. in einer festen Partnerschaft,\nengaged. verlobt,\nmarried. verheiratet,\nunclear_status. unklarer Status,\ndont_know. weiß ich nicht",
      "maxValue": "unclear_status",
      "minValue": "dont_know",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_relationship_to_anchor",
      "description": "Wie stehen Sie zu __`r person`__?",
      "value": "loose_acquaintance. kennen uns nur vom Sehen,\nacquaintance. besser bekannt,\nfriend. befreundet,\nbiological_relative. biologisch verwandt (e.g. Mutter),\nnonbiological_relative. nichtbiologisch verwandt (e.g. Stiefschwester, Adoptivmutter, angeheiratete Tante),\nromantic_short_term_relationship. haben eine romantische Kurzzeitbeziehung,\nromantic_long_term_relationship. haben eine romantische Langzeitbeziehung",
      "maxValue": "romantic_short_term_relationship",
      "minValue": "acquaintance",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_kinship",
      "description": "Wie sind Sie mit __`r person`__ verwandt?",
      "value": "mother. Mutter,\nfather. Vater,\nbrother. Bruder,\nsister. Schwester,\naunt. Tante,\nuncle. Onkel,\ncousin. Cousin(e),\ndaughter. Tochter,\nson. Sohn,\nnephew. Neffe,\nniece. Nichte",
      "maxValue": "uncle",
      "minValue": "aunt",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_romantic_experience",
      "description": "Hatten Sie und __`r person`__ je eine romantische oder sexuelle Erfahrung miteinander?\n<small>Wählen Sie bitte die \"höchste\" zutreffende Antwort.<\/small>",
      "value": "none. nein,\nflirt. ja, Flirt,\ndate. ja, ein/mehrere Dates oder ähnliches,\nmake_out. ja, sexuelle Handlungen (bspw. Küssen),\nsex. ja, Sex",
      "maxValue": "sex",
      "minValue": "date",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_height",
      "description": "Was ist die ungefähre Körpergröße von __`r person`__ in cm (ohne Schuhe)?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_weight",
      "description": "Was ist das ungefähre Gewicht von __`r person`__ in kg (ohne Kleidung)?",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_attractiveness_short_term",
      "description": "Ich finde __`r person`__ attraktiv für einen One-Night-Stand oder eine kurze sexuelle Affäre mit mir.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_attractiveness_long_term",
      "description": "Ich finde __`r person`__ attraktiv für eine langfristige Beziehung (feste Partnerschaft, Ehe, ...) mit mir.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_attractive_body",
      "description": "__`r person`__ hat einen attraktiven Körper und Gesicht.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_kindness",
      "description": "__`r person`__ ist warmherzig, ein guter Mensch.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_education",
      "description": "__`r person`__ ist gebildet, war gut in der Schule/Universität.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_extraversion",
      "description": "__`r person`__ ist gesellig, gerne unter Menschen.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_dominance",
      "description": "__`r person`__ ist dominant.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_strength",
      "description": "__`r person`__ ist körperlich stärker als viele andere Männer.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_financial",
      "description": "__`r person`__ verdient gut oder wird einmal gut verdienen.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_faithful",
      "description": "__`r person`__ wäre in einer Beziehung treu.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_funny",
      "description": "__`r person`__ ist lustig, unterhaltsam.",
      "value": "1. 1: trifft überhaupt nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft voll und ganz zu,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "person_notes",
      "description": "Wir haben versucht, es kurz zu halten. Haben Sie noch Anmerkungen zu __`r person`__, die durch unsere Fragen nicht oder nicht gut erfasst wurden?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    }
  ]
}`

Follow-up survey

At the end of the diary, participants were debriefed and answered these follow-up questions.

Metadata

Description

Dataset name: s4_followup

The dataset has N=1171 rows and 45 columns. 0 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
created
modified
ended
expired
hypothesis_guess
wont_leak
medication
medication_name
special_days
honest_answers
honest_answers_name
illness
illness_name
breakup
new_relationship
change_contraception
change_contraception_to
aware_fertile_phases_number
aware_fertile_1_start
aware_fertile_1_end
aware_fertile_2_start
aware_fertile_2_end
aware_fertile_3_start
aware_fertile_3_end
aware_fertile_reason_unusual
follicular_phase_length
follicular_phase_length_certainty
luteal_phase_length
luteal_phase_length_certainty
aware_mittelschmerz
aware_cycle_changes
aware_cycle_changes_mens
aware_cycle_changes_ovulation
aware_fertile_effects
let_hormones_affect_behavior1R
let_hormones_affect_behavior2
let_mens_affect_behavior
hormones_may_affect_me1
hormones_may_affect_me2R
feedback_for_us
want_more_info
let_hormones_affect_behavior
hormones_may_affect_me
short

Survey overview

1140 completed rows, 1167 who entered any information, 4 only viewed the first page. There are 23 expired rows (people who did not finish filling out in the requested time frame). In total, there are 1171 rows including unfinished and expired rows.

There were 1171 unique participants, of which 1140 finished filling out at least one survey.

This survey was not repeated.

The first session started on 2016-07-12 01:07:06, the last session on 2017-04-13 14:25:39.

Starting date times

People took on average 1395.71 minutes (median 8.27) to answer the survey.

Duration people took for answering the survey

#Variables

hypothesis_guess

Abschlussfragebogen

Worum glauben Sie ging es in dieser Studie hauptsächlich?

Wenn Sie keinen Verdacht haben oder jetzt zum ersten Mal darüber nachdenken, lassen sie dieses Feld einfach leer. Sie können uns später gern noch weitere Kommentare hinterlassen.

Distribution

Distribution of values for hypothesis_guess

633 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
hypothesis_guess	## Abschlussfragebogen Worum glauben Sie ging es in dieser Studie hauptsächlich? Wenn Sie keinen Verdacht haben oder jetzt zum ersten Mal darüber nachdenken, lassen sie dieses Feld einfach leer. Sie können uns später gern noch weitere Kommentare hinterlassen.	textarea	character	1			1	633	0.4594	537	0	1	1726	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	hypothesis_guess	Abschlussfragebogen Worum glauben Sie ging es in dieser Studie hauptsächlich? Wenn Sie keinen Verdacht haben oder jetzt zum ersten Mal darüber nachdenken, lassen sie dieses Feld einfach leer. Sie können uns später gern noch weitere Kommentare hinterlassen.	1			1

Value labels

Response choices
name	value

wont_leak

Können Sie uns versprechen in den kommenden drei Monaten noch mit niemandem über die Hypothesen der Studie und die anderen oben genannten Gesichtspunkte zu sprechen? Dadurch würden Sie uns sehr helfen, unvoreingenommene oder unbewusst beeinflusste Antworten auf unsere Fragen zu erhalten.

Distribution

Distribution of values for wont_leak

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		wont_leak	Können Sie uns versprechen in den kommenden drei Monaten noch mit niemandem über die Hypothesen der Studie und die anderen oben genannten Gesichtspunkte zu sprechen? Dadurch würden Sie uns sehr helfen, unvoreingenommene oder unbewusst beeinflusste Antworten auf unsere Fragen zu erhalten.	0			4

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

medication

Haben Sie innerhalb des letzten Monats Arzneimittel eingenommen?

Distribution

Distribution of values for medication

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		medication	Haben Sie innerhalb des letzten Monats Arzneimittel eingenommen?	0			5

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

medication_name

Distribution

Distribution of values for medication_name

628 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
medication_name	character	628	0.4637	450	0	3	200	0	NA

special_days

Gab es innerhalb des Zeitraums der Studie besondere oder außergewöhnliche Ereignisse, die wir wissen sollten um Ihre Beziehungsdynamiken und anderen Angaben richtig einzuordnen?

Distribution

Distribution of values for special_days

506 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
special_days	Gab es innerhalb des Zeitraums der Studie besondere oder außergewöhnliche Ereignisse, die wir wissen sollten um Ihre Beziehungsdynamiken und anderen Angaben richtig einzuordnen?	textarea	character	1			7	506	0.5679	568	0	1	1293	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	special_days	Gab es innerhalb des Zeitraums der Studie besondere oder außergewöhnliche Ereignisse, die wir wissen sollten um Ihre Beziehungsdynamiken und anderen Angaben richtig einzuordnen?	1			7

Value labels

Response choices
name	value

honest_answers

Haben Sie auf alle Fragen der Studie (inkl. Vorabfragebogen und täglicher Fragebogen) ehrlich geantwortet (so gut es ging)? Ihnen entstehen keine Nachteile bei der Entgeltung oder Verlosung durch eine Verneinung dieser Frage.

Distribution

Distribution of values for honest_answers

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		honest_answers	Haben Sie auf alle Fragen der Studie (inkl. Vorabfragebogen und täglicher Fragebogen) ehrlich geantwortet (so gut es ging)? Ihnen entstehen keine Nachteile bei der Entgeltung oder Verlosung durch eine Verneinung dieser Frage.	0			8

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

honest_answers_name

Wenn nein, beschreiben Sie bitte bei welchen Fragen Sie nicht ehrlich geantwortet haben, falls möglich.

Distribution

Distribution of values for honest_answers_name

1167 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
honest_answers_name	Wenn nein, beschreiben Sie bitte bei welchen Fragen Sie nicht ehrlich geantwortet haben, falls möglich.	textarea	character	0	honest_answers ==0		9	1167	0.0034	4	0	60	484	0

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	honest_answers_name	Wenn nein, beschreiben Sie bitte bei welchen Fragen Sie nicht ehrlich geantwortet haben, falls möglich.	0	honest_answers ==0		9

Value labels

Response choices
name	value

illness

Waren Sie innerhalb des letzten Monats krank?

Distribution

Distribution of values for illness

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		illness	Waren Sie innerhalb des letzten Monats krank?	0			10

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

illness_name

Wenn ja, woran litten Sie?

Distribution

Distribution of values for illness_name

652 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
illness_name	Wenn ja, woran litten Sie?	text	character	0	illness == 1		11	652	0.4432	289	0	3	256	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	illness_name	Wenn ja, woran litten Sie?	0	illness == 1		11

Value labels

Response choices
name	value

breakup

Haben Sie sich innerhalb des letzten Monats von Ihrem Partner getrennt?

Distribution

Distribution of values for breakup

416 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for breakup

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		breakup	Haben Sie sich innerhalb des letzten Monats von Ihrem Partner getrennt?	0	s1_demo$hetero_relationship		12

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

new_relationship

Sind Sie im letzten Monat eine neue Partnerschaft eingegangen?

Distribution

Distribution of values for new_relationship

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		new_relationship	Sind Sie im letzten Monat eine neue Partnerschaft eingegangen?	0			13

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

change_contraception

Haben Sie innerhalb des letzten Monats Ihre Verhütungsmethode gewechselt?

Distribution

Distribution of values for change_contraception

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
mc		change_contraception	Haben Sie innerhalb des letzten Monats Ihre Verhütungsmethode gewechselt?	0			14

Value labels

Response choices
name	value
Nein	0
Ja	1
Item was never rendered for this user.	NA

change_contraception_to

Welche Verhütungsmethode verwenden Sie nun?

Distribution

Distribution of values for change_contraception_to

1133 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
change_contraception_to	Welche Verhütungsmethode verwenden Sie nun?	text	character	0	change_contraception == 1		15	1133	0.0325	31	0	5	126	0

Item

Item options
type	name	label	optional	showif	value	item_order
text	change_contraception_to	Welche Verhütungsmethode verwenden Sie nun?	0	change_contraception == 1		15

Value labels

Response choices
name	value

aware_fertile_phases_number

Wieviele fruchtbare Phasen oder “Fenster” haben Sie bei sich während des Studienzeitraums beobachtet? Sie hatten angegeben, dass Sie eine Verhütungsmethode benutzen, bei der Sie auf Ihre fruchtbare Phase achten oder dass Sie eine Zyklus-App benutzen.

Distribution

Distribution of values for aware_fertile_phases_number

801 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for aware_fertile_phases_number

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
number	0,6,1	aware_fertile_phases_number	Wieviele fruchtbare Phasen oder “Fenster” haben Sie bei sich während des Studienzeitraums beobachtet? <small>Sie hatten angegeben, dass Sie eine Verhütungsmethode benutzen, bei der Sie auf Ihre fruchtbare Phase achten oder dass Sie eine Zyklus-App benutzen.</small>	0	s1_demo$contraception_method %contains% "awareness" \| s1_demo$contraception_app == 1		16

Value labels

Response choices
name	value
Item was not shown to this user.	NA
Item was never rendered for this user.	NA

aware_fertile_1_start

Erstes Fenster: von

Distribution

## 159  unique, categorical values, so not shown.

867 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_1_start	Erstes Fenster: von	date	-3months,now	Date	0	aware_fertile_phases_number > 0		17	left200 right300 align_horizontally	867	0.2596	159	2016-04-17	2016-09-15	2017-01-27

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_1_start	Erstes Fenster: von	0	left200 right300 align_horizontally	aware_fertile_phases_number > 0		17

Value labels

Response choices
name	value

aware_fertile_1_end

bis

Distribution

## 161  unique, categorical values, so not shown.

867 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_1_end	bis	date	-3months,now	Date	0	aware_fertile_phases_number > 0		18	left50 right300 align_horizontally	867	0.2596	161	2016-04-23	2016-09-24	2017-02-21

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_1_end	bis	0	left50 right300 align_horizontally	aware_fertile_phases_number > 0		18

Value labels

Response choices
name	value

aware_fertile_2_start

Zweites Fenster: von

Distribution

## 158  unique, categorical values, so not shown.

881 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_2_start	Zweites Fenster: von	date	-3months,now	Date	0	aware_fertile_phases_number > 1		20	left200 right300 align_horizontally	881	0.2477	158	2016-05-16	2016-10-13	2017-02-28

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_2_start	Zweites Fenster: von	0	left200 right300 align_horizontally	aware_fertile_phases_number > 1		20

Value labels

Response choices
name	value

aware_fertile_2_end

bis

Distribution

## 150  unique, categorical values, so not shown.

881 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_2_end	bis	date	-3months,now	Date	0	aware_fertile_phases_number > 1		21	left50 right300 align_horizontally	881	0.2477	150	2016-05-24	2016-10-18	2017-03-05

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_2_end	bis	0	left50 right300 align_horizontally	aware_fertile_phases_number > 1		21

Value labels

Response choices
name	value

aware_fertile_3_start

Drittes Fenster: von

Distribution

## 114  unique, categorical values, so not shown.

1013 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_3_start	Drittes Fenster: von	date	-3months,now	Date	0	aware_fertile_phases_number > 2		23	left200 right300 align_horizontally	1013	0.1349	114	2016-06-15	2016-11-03	2017-03-13

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_3_start	Drittes Fenster: von	0	left200 right300 align_horizontally	aware_fertile_phases_number > 2		23

Value labels

Response choices
name	value

aware_fertile_3_end

bis

Distribution

## 114  unique, categorical values, so not shown.

1013 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	min	median	max
aware_fertile_3_end	bis	date	-3months,now	Date	0	aware_fertile_phases_number > 2		24	left50 right300 align_horizontally	1013	0.1349	114	2016-06-19	2016-11-06	2017-03-19

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
date	-3months,now	aware_fertile_3_end	bis	0	left50 right300 align_horizontally	aware_fertile_phases_number > 2		24

Value labels

Response choices
name	value

aware_fertile_reason_unusual

Sie haben angegeben weniger als 2 oder mehr als 3 fruchtbare Fenster in den 70 Tagen des Tagebuchs beobachtet zu haben. Das ist über einen Zeitraum von 70 Tagen eher ungewöhnlich, und manche Frauen sind sich der Gründe dafür bewusst. Wenn Sie den Grund genauer kennen, können Sie ihn hier erläutern.

Distribution

Distribution of values for aware_fertile_reason_unusual

1085 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	class	n_missing	complete_rate	n_unique	empty	min	max	whitespace
aware_fertile_reason_unusual	Sie haben angegeben weniger als 2 oder mehr als 3 fruchtbare Fenster in den 70 Tagen des Tagebuchs beobachtet zu haben. Das ist über einen Zeitraum von 70 Tagen eher ungewöhnlich, und manche Frauen sind sich der Gründe dafür bewusst. Wenn Sie den Grund genauer kennen, können Sie ihn hier erläutern.	textarea	character	0	aware_fertile_phases_number !== "" && (aware_fertile_phases_number > 3 \|\| aware_fertile_phases_number < 2) //js_only		26	align_horizontally left300 right400	1085	0.0734	84	0	1	1490	0

Item

Item options
type	name	label	optional	class	showif	value	item_order
textarea	aware_fertile_reason_unusual	Sie haben angegeben weniger als 2 oder mehr als 3 fruchtbare Fenster in den 70 Tagen des Tagebuchs beobachtet zu haben. Das ist über einen Zeitraum von 70 Tagen eher ungewöhnlich, und manche Frauen sind sich der Gründe dafür bewusst. Wenn Sie den Grund genauer kennen, können Sie ihn hier erläutern.	0	align_horizontally left300 right400	aware_fertile_phases_number !== "" && (aware_fertile_phases_number > 3 \|\| aware_fertile_phases_number < 2) //js_only		26

Value labels

Response choices
name	value

follicular_phase_length

Wie lange dauert Ihre Follikelphase (1. Zyklushälfte: Reifungsphase der Eibläschen, endet mit dem Eisprung; meist zwischen 12-21 Tagen)? Falls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.

Distribution

Distribution of values for follicular_phase_length

971 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for follicular_phase_length

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
number	7,50,1	follicular_phase_length	Wie lange dauert Ihre Follikelphase (1. Zyklushälfte: Reifungsphase der Eibläschen, endet mit dem Eisprung; meist zwischen 12-21 Tagen)? Falls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.	1	left300 right150	s1_demo$contraception_method %contains% "awareness" \| s1_demo$contraception_app == 1		28

Value labels

Response choices
name	value
Item was not shown to this user.	NA
User skipped this item.	NA
Item was never rendered for this user.	NA

follicular_phase_length_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for follicular_phase_length_certainty

922 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for follicular_phase_length_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	follicular_phase_length_certainty	Wie sicher sind Sie sich bei dieser Angabe?	1	s1_demo$contraception_method %contains% "awareness" \| s1_demo$contraception_app == 1		29

Value labels

Response choices
name	value
stimmt genau	1
±1 Tag	2
±2 Tage	3
±3 Tage	4
±4 Tage	5
±5 Tage	6
±6 Tage	7
unsicherer	8
Item was not shown to this user.	NA
User skipped this item.	NA
Item was never rendered for this user.	NA

luteal_phase_length

Wie lange dauert Ihre Lutealphase (2. Zyklushälfte: Gelbkörperphase, beginnt mit dem Eisprung; meist zwischen 12-16 Tagen)? Falls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.

Distribution

Distribution of values for luteal_phase_length

983 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for luteal_phase_length

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
number	7,50,1	luteal_phase_length	Wie lange dauert Ihre Lutealphase (2. Zyklushälfte: Gelbkörperphase, beginnt mit dem Eisprung; meist zwischen 12-16 Tagen)? Falls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.	1	right150 left300	s1_demo$contraception_method %contains% "awareness" \| s1_demo$contraception_app == 1		30

Value labels

Response choices
name	value
Item was not shown to this user.	NA
User skipped this item.	NA
Item was never rendered for this user.	NA

luteal_phase_length_certainty

Wie sicher sind Sie sich bei dieser Angabe?

Distribution

Distribution of values for luteal_phase_length_certainty

940 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Missing value types

Plot of missing values for luteal_phase_length_certainty

Item

Item options
type	name	label	optional	showif	value	item_order
mc_button	luteal_phase_length_certainty	Wie sicher sind Sie sich bei dieser Angabe?	1	s1_demo$contraception_method %contains% "awareness" \| s1_demo$contraception_app == 1		31

Value labels

Response choices
name	value
stimmt genau	1
±1 Tag	2
±2 Tage	3
±3 Tage	4
±4 Tage	5
±5 Tage	6
±6 Tage	7
unsicherer	8
Item was not shown to this user.	NA
User skipped this item.	NA
Item was never rendered for this user.	NA

aware_mittelschmerz

Empfinden Sie Mittelschmerz, also einen Schmerz im Unterleib, der in der Zyklusmitte zur Ovulation auftritt, und normalerweise von einigen Stunden bis zu mehreren Tagen andauert?

Distribution

Distribution of values for aware_mittelschmerz

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	class	showif	value	item_order
mc_button		aware_mittelschmerz	Empfinden Sie Mittelschmerz, also einen Schmerz im Unterleib, der in der Zyklusmitte zur Ovulation auftritt, und normalerweise von einigen Stunden bis zu mehreren Tagen andauert?	0	mc_vertical			32

Value labels

Response choices
name	value
1	1_every_cycle
2	2_every_other_cycle
3	3_sometimes
4	4_rarely
5	5_no_almost_never
6	6_no_not_sure
7	7_no_never

aware_cycle_changes

Ich erlebe hormonelle Schwankungen im Zyklus.

Distribution

Distribution of values for aware_cycle_changes

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	aware_cycle_changes	Ich erlebe hormonelle Schwankungen im Zyklus.	0			33

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

aware_cycle_changes_mens

Ich bemerke hormonelle Veränderungen an mir vor und/oder während der Menstruation.

Distribution

Distribution of values for aware_cycle_changes_mens

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	aware_cycle_changes_mens	Ich bemerke hormonelle Veränderungen an mir vor und/oder während der Menstruation.	0			34

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

aware_cycle_changes_ovulation

Ich bemerke hormonelle Veränderungen an mir in der Zyklusmitte, wenn ich fruchtbar bin.

Distribution

Distribution of values for aware_cycle_changes_ovulation

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	aware_cycle_changes_ovulation	Ich bemerke hormonelle Veränderungen an mir in der Zyklusmitte, wenn ich fruchtbar bin.	0			35

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

aware_fertile_effects

Sie nehmen bei sich selbst psychologische oder physiologische Veränderungen war, wenn Sie fruchtbar sind oder generell über den Zyklus hinweg? Können Sie diese benennen?

Distribution

Distribution of values for aware_fertile_effects

355 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
aware_fertile_effects	Sie nehmen bei sich selbst psychologische oder physiologische Veränderungen war, wenn Sie fruchtbar sind oder generell über den Zyklus hinweg? Können Sie diese benennen?	textarea	character	1	aware_cycle_changes > 1 \| aware_cycle_changes_ovulation > 1 \| aware_cycle_changes_mens > 1		36	355	0.6968	784	0	2	2547	1

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	aware_fertile_effects	Sie nehmen bei sich selbst psychologische oder physiologische Veränderungen war, wenn Sie fruchtbar sind oder generell über den Zyklus hinweg? Können Sie diese benennen?	1	aware_cycle_changes > 1 \| aware_cycle_changes_ovulation > 1 \| aware_cycle_changes_mens > 1		36

Value labels

Response choices
name	value

let_mens_affect_behavior

In den Tagen vor der Menstruation lasse ich schon mal meine schlechte Laune an anderen aus.

Distribution

Distribution of values for let_mens_affect_behavior

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	type_options	name	label	optional	showif	value	item_order
rating_button	5 agree	let_mens_affect_behavior	In den Tagen vor der Menstruation lasse ich schon mal meine schlechte Laune an anderen aus.	0			39

Value labels

Response choices
name	value
1: trifft gar nicht zu	1
2	2
3	3
4	4
5: trifft völlig zu	5
Item was never rendered for this user.	NA

feedback_for_us

Wenn Sie nun noch generelles Feedback an uns haben, benutzen Sie bitte diese Textbox.

Distribution

Distribution of values for feedback_for_us

976 missing values.

Summary statistics

name	label	type	data_type	optional	showif	value	item_order	n_missing	complete_rate	n_unique	empty	min	max	whitespace
feedback_for_us	Wenn Sie nun noch generelles Feedback an uns haben, benutzen Sie bitte diese Textbox.	textarea	character	1			43	976	0.1665	194	0	1	1796	2

Item

Item options
type	name	label	optional	showif	value	item_order
textarea	feedback_for_us	Wenn Sie nun noch generelles Feedback an uns haben, benutzen Sie bitte diese Textbox.	1			43

Value labels

Response choices
name	value

want_more_info

Bitte kreuzen Sie dieses Feld an, wenn Sie nach Auswertung der Ergebnisse von uns per Email erfahren wollen, was wir herausgefunden haben. Wir melden uns dann im Spätsommer bei Ihnen, wenn die Datenauswertung abgeschlossen ist.

Distribution

Distribution of values for want_more_info

31 missing values.

Summary statistics

## Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class '"haven_labelled"' to a data.frame

## Error in names(df) = html_item_name: names() applied to a non-vector

## Error in (skimr::skim_with(haven_labelled = haven_labelled_sfl, haven_labelled_spss = haven_labelled_sfl, : inherits(data, "data.frame") is not TRUE

## Error in cb_table$value_labels <- NULL: object 'cb_table' not found

## Error in exists("value_labels", metadata_table): object 'cb_table' not found

Item

Item options
type	name	label	optional	class	showif	value	item_order
check_button	want_more_info	Bitte kreuzen Sie dieses Feld an, wenn Sie nach Auswertung der Ergebnisse von uns per Email erfahren wollen, was wir herausgefunden haben. Wir melden uns dann im Spätsommer bei Ihnen, wenn die Datenauswertung abgeschlossen ist.	1	left600			45

Value labels

Response choices
name	value
Item was never rendered for this user.	NA

Scale: let_hormones_affect_behavior

Overview

Reliability: .

Missing: 31.

Likert plot of scale let_hormones_affect_behavior items

Distribution of scale let_hormones_affect_behavior

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	let_hormones_affect_behavior1R & let_hormones_affect_behavior2
Observations:	1140
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures


Spearman Brown coefficient:	0.47
Coefficient Alpha:	0.46
Pearson Correlation:	0.30

Eigen values

1.305 & 0.695

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
let_hormones_affect_behavior1R	3.22017543859649	3	1.1955539639265	1.09341390329852	1	0.0323841249272532	1	2	4	5	-0.238594723437503	-0.563567302814599	0.151315789473684	1140	0	1140
let_hormones_affect_behavior2	2.91315789473684	3	1.84056420682963	1.35667395008146	2	0.0401812145907873	1	1	4	5	-0.00918774181158757	-1.25166408711994	0.105263157894737	1140	0	1140

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
let_hormones_affect_behavior1R	In meinem Verhalten lasse ich mich nicht von meinen Hormonen leiten.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			37	31	0.9735	1	3	5	3.220	1.093	6	▂▅▁▇▁▇▁▃
let_hormones_affect_behavior2	Wenn meine Hormone verrückt spielen, kommt es schonmal vor, dass ich über die Stränge schlage.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			38	31	0.9735	1	3	5	2.913	1.357	6	▆▆▁▆▁▇▁▅

Scale: hormones_may_affect_me

Overview

Reliability: .

Missing: 31.

Likert plot of scale hormones_may_affect_me items

Distribution of scale hormones_may_affect_me

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale


Dataframe:	res$dat
Items:	hormones_may_affect_me1 & hormones_may_affect_me2R
Observations:	1140
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures


Spearman Brown coefficient:	0.59
Coefficient Alpha:	0.59
Pearson Correlation:	0.42

Eigen values

1.416 & 0.584

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
hormones_may_affect_me1	2.47894736842105	2	1.2541657039878	1.11989539868141	1	0.0331684391308253	1	1	3	5	0.375859182256098	-0.58276766283123	0.148245614035088	1140	0	1140
hormones_may_affect_me2R	2.58157894736842	3	1.37086317637817	1.17083866368436	1	0.0346772484235192	1	2	4	5	0.289593757931042	-0.799430647478316	0.136842105263158	1140	0	1140

Scattermatrix

Scatterplot

Summary statistics

name	label	type	type_options	data_type	value_labels	optional	showif	value	item_order	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
hormones_may_affect_me1	Ich finde es OK, mich einfach mal von meinen Hormonen leiten zu lassen.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 2. 2, 3. 3, 4. 4, 5. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			40	31	0.9735	1	2	5	2.479	1.120	6	▆▇▁▇▁▃▁▁
hormones_may_affect_me2R	Ein hormoneller Ausnahmezustand ist für mich keine Entschuldigung, mich anders zu verhalten.	rating_button	5 agree	haven_labelled	1: trifft gar nicht zu, 4. 2, 3. 3, 2. 4, 1. 5: trifft völlig zu, NA. Item was never rendered for this user.	0			41	31	0.9735	1	3	5	2.582	1.171	6	▆▇▁▇▁▅▁▂

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	1171	0	7	7	0	NA

Missingness report

## # A tibble: 23 x 45
##    description modified ended wont_leak medication honest_answers illness new_relationship change_contrace…
##    <chr>          <dbl> <dbl>     <dbl>      <dbl>          <dbl>   <dbl>            <dbl>            <dbl>
##  1 Missing va…        4    31        31         31             31      31               31               31
##  2 Missing va…        1     1         1          1              1       1                1                1
##  3 Missing va…        1     1         1          1              1       1                1                1
##  4 Missing va…        1     1         1          1              1       1                1                1
##  5 Missing va…        1     1         1          1              1       1                1                1
##  6 Missing va…        1     1         1          1              1       1                1                1
##  7 Missing va…        1     1         1          1              1       1                1                1
##  8 Missing va…        1     1         1          1              1       1                1                1
##  9 Missing va…        1     0         0          0              0       0                0                0
## 10 Missing va…        1     1         1          1              1       1                1                1
## # … with 13 more rows, and 36 more variables: aware_mittelschmerz <dbl>, aware_cycle_changes <dbl>,
## #   aware_cycle_changes_mens <dbl>, aware_cycle_changes_ovulation <dbl>,
## #   let_hormones_affect_behavior1R <dbl>, let_hormones_affect_behavior2 <dbl>,
## #   let_mens_affect_behavior <dbl>, hormones_may_affect_me1 <dbl>, hormones_may_affect_me2R <dbl>,
## #   want_more_info <dbl>, let_hormones_affect_behavior <dbl>, hormones_may_affect_me <dbl>,
## #   aware_fertile_effects <dbl>, breakup <dbl>, special_days <dbl>, medication_name <dbl>,
## #   hypothesis_guess <dbl>, illness_name <dbl>, aware_fertile_phases_number <dbl>,
## #   aware_fertile_1_start <dbl>, aware_fertile_1_end <dbl>, aware_fertile_2_start <dbl>,
## #   aware_fertile_2_end <dbl>, follicular_phase_length_certainty <dbl>, luteal_phase_length_certainty <dbl>,
## #   follicular_phase_length <dbl>, feedback_for_us <dbl>, luteal_phase_length <dbl>,
## #   aware_fertile_3_start <dbl>, aware_fertile_3_end <dbl>, aware_fertile_reason_unusual <dbl>,
## #   change_contraception_to <dbl>, expired <dbl>, honest_answers_name <dbl>, var_miss <dbl>, n_miss <dbl>

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "s4_followup",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=1171 rows and 45 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "created", "modified", "ended", "expired", "hypothesis_guess", "wont_leak", "medication", "medication_name", "special_days", "honest_answers", "honest_answers_name", "illness", "illness_name", "breakup", "new_relationship", "change_contraception", "change_contraception_to", "aware_fertile_phases_number", "aware_fertile_1_start", "aware_fertile_1_end", "aware_fertile_2_start", "aware_fertile_2_end", "aware_fertile_3_start", "aware_fertile_3_end", "aware_fertile_reason_unusual", "follicular_phase_length", "follicular_phase_length_certainty", "luteal_phase_length", "luteal_phase_length_certainty", "aware_mittelschmerz", "aware_cycle_changes", "aware_cycle_changes_mens", "aware_cycle_changes_ovulation", "aware_fertile_effects", "let_hormones_affect_behavior1R", "let_hormones_affect_behavior2", "let_mens_affect_behavior", "hormones_may_affect_me1", "hormones_may_affect_me2R", "feedback_for_us", "want_more_info", "let_hormones_affect_behavior", "hormones_may_affect_me", "short"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "hypothesis_guess",
      "description": "## Abschlussfragebogen\n\nWorum glauben Sie ging es in dieser Studie hauptsächlich?\n\nWenn Sie keinen Verdacht haben oder jetzt zum ersten Mal darüber nachdenken, lassen sie dieses Feld einfach leer. Sie können uns später gern noch weitere Kommentare hinterlassen.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "wont_leak",
      "description": "Können Sie uns versprechen in den kommenden drei Monaten noch mit niemandem über die Hypothesen der Studie und die anderen oben genannten Gesichtspunkte zu sprechen? Dadurch würden Sie uns sehr helfen, unvoreingenommene oder unbewusst beeinflusste Antworten auf unsere Fragen zu erhalten.",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "medication",
      "description": "Haben Sie innerhalb des letzten Monats Arzneimittel eingenommen?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "medication_name",
      "@type": "propertyValue"
    },
    {
      "name": "special_days",
      "description": "Gab es innerhalb des Zeitraums der Studie besondere oder außergewöhnliche Ereignisse, die wir wissen sollten um Ihre Beziehungsdynamiken und anderen Angaben richtig einzuordnen?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "honest_answers",
      "description": "Haben Sie auf alle Fragen der Studie (inkl. Vorabfragebogen und täglicher Fragebogen) ehrlich geantwortet (so gut es ging)?\nIhnen entstehen keine Nachteile bei der Entgeltung oder Verlosung durch eine Verneinung dieser Frage.",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "honest_answers_name",
      "description": "Wenn nein, beschreiben Sie bitte bei welchen Fragen Sie nicht ehrlich geantwortet haben, falls möglich.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "illness",
      "description": "Waren Sie innerhalb des letzten Monats krank?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "illness_name",
      "description": "Wenn ja, woran litten Sie?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "breakup",
      "description": "Haben Sie sich innerhalb des letzten Monats von Ihrem Partner getrennt?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "new_relationship",
      "description": "Sind Sie im letzten Monat eine neue Partnerschaft eingegangen?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "change_contraception",
      "description": "Haben Sie innerhalb des letzten Monats Ihre Verhütungsmethode gewechselt?",
      "value": "0. Nein,\n1. Ja,\nNA. Item was never rendered for this user.",
      "maxValue": 1,
      "minValue": 0,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "change_contraception_to",
      "description": "Welche Verhütungsmethode verwenden Sie nun?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_phases_number",
      "description": "\nWieviele fruchtbare Phasen oder \"Fenster\" haben Sie bei sich während des Studienzeitraums beobachtet?\n<small>Sie hatten angegeben, dass Sie eine Verhütungsmethode benutzen, bei der Sie auf Ihre fruchtbare Phase achten oder dass Sie eine Zyklus-App benutzen.<\/small>",
      "value": "NA. Item was not shown to this user.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_1_start",
      "description": "Erstes Fenster: von",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_1_end",
      "description": "bis",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_2_start",
      "description": "Zweites Fenster: von",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_2_end",
      "description": "bis",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_3_start",
      "description": "Drittes Fenster: von",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_3_end",
      "description": "bis",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_reason_unusual",
      "description": "Sie haben angegeben weniger als 2 oder mehr als 3 fruchtbare Fenster in den 70 Tagen des Tagebuchs beobachtet zu haben. Das ist über einen Zeitraum von 70 Tagen eher ungewöhnlich, und manche Frauen sind sich der Gründe dafür bewusst. Wenn Sie den Grund genauer kennen, können Sie ihn hier erläutern.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "follicular_phase_length",
      "description": "Wie lange dauert Ihre Follikelphase (1. Zyklushälfte: Reifungsphase der Eibläschen, endet  mit dem Eisprung; meist zwischen 12-21 Tagen)?\nFalls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.",
      "value": "NA. Item was not shown to this user.,\nNA. User skipped this item.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "follicular_phase_length_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1 Tag,\n3. ±2 Tage,\n4. ±3 Tage,\n5. ±4 Tage,\n6. ±5 Tage,\n7. ±6 Tage,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. User skipped this item.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "luteal_phase_length",
      "description": "Wie lange dauert Ihre  Lutealphase (2. Zyklushälfte: Gelbkörperphase, beginnt mit  dem Eisprung; meist zwischen 12-16 Tagen)?\nFalls Sie dazu keine Angaben machen können, lassen Sie dieses Feld bitte frei.",
      "value": "NA. Item was not shown to this user.,\nNA. User skipped this item.,\nNA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "luteal_phase_length_certainty",
      "description": "Wie sicher sind Sie sich bei dieser Angabe?",
      "value": "1. stimmt genau,\n2. ±1 Tag,\n3. ±2 Tage,\n4. ±3 Tage,\n5. ±4 Tage,\n6. ±5 Tage,\n7. ±6 Tage,\n8. unsicherer,\nNA. Item was not shown to this user.,\nNA. User skipped this item.,\nNA. Item was never rendered for this user.",
      "maxValue": 8,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_mittelschmerz",
      "description": "Empfinden Sie Mittelschmerz, also einen Schmerz im Unterleib, der in der Zyklusmitte zur Ovulation auftritt, und normalerweise von einigen Stunden bis zu mehreren Tagen andauert?",
      "value": "1_every_cycle. ja, jeden Zyklus,\n2_every_other_cycle. ja, ungefähr jeden zweiten Zyklus,\n3_sometimes. ja, manchmal,\n4_rarely. ja, aber selten,\n5_no_almost_never. nein, so gut wie nie,\n6_no_not_sure. nein, bin mir nicht sicher,\n7_no_never. nein, überhaupt nie",
      "maxValue": "7_no_never",
      "minValue": "1_every_cycle",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_cycle_changes",
      "description": "Ich erlebe hormonelle Schwankungen im Zyklus.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_cycle_changes_mens",
      "description": "Ich bemerke hormonelle Veränderungen an mir vor und/oder während der Menstruation.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_cycle_changes_ovulation",
      "description": "Ich bemerke hormonelle Veränderungen an mir in der Zyklusmitte, wenn ich fruchtbar bin.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "aware_fertile_effects",
      "description": "Sie nehmen bei sich selbst psychologische oder physiologische Veränderungen war, wenn Sie fruchtbar sind oder generell über den Zyklus hinweg? Können Sie diese benennen?",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "let_hormones_affect_behavior1R",
      "description": "In meinem Verhalten lasse ich mich nicht von meinen Hormonen leiten.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "let_hormones_affect_behavior2",
      "description": "Wenn meine Hormone verrückt spielen, kommt es schonmal vor, dass ich über die Stränge schlage.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "let_mens_affect_behavior",
      "description": "In den Tagen vor der Menstruation lasse ich schon mal meine schlechte Laune an anderen aus.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hormones_may_affect_me1",
      "description": "Ich finde es OK, mich einfach mal von meinen Hormonen leiten zu lassen.",
      "value": "1. 1: trifft gar nicht zu,\n2. 2,\n3. 3,\n4. 4,\n5. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "hormones_may_affect_me2R",
      "description": "Ein hormoneller Ausnahmezustand ist für mich keine Entschuldigung, mich anders zu verhalten.",
      "value": "5. 1: trifft gar nicht zu,\n4. 2,\n3. 3,\n2. 4,\n1. 5: trifft völlig zu,\nNA. Item was never rendered for this user.",
      "maxValue": 5,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "feedback_for_us",
      "description": "Wenn Sie nun noch generelles Feedback an uns haben, benutzen Sie bitte diese Textbox.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "want_more_info",
      "description": "Bitte kreuzen Sie dieses Feld an, wenn Sie nach Auswertung der Ergebnisse von uns per Email erfahren wollen, was wir herausgefunden haben. Wir melden uns dann im Spätsommer bei Ihnen, wenn die Datenauswertung abgeschlossen ist.",
      "value": "NA. Item was never rendered for this user.",
      "maxValue": "-Inf",
      "minValue": "Inf",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "let_hormones_affect_behavior",
      "description": "2 let_hormones_affect_behavior items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "hormones_may_affect_me",
      "description": "2 hormones_may_affect_me items averaged with aggregation_function",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    }
  ]
}`

Menstruation follow-up

To be able to backward-count from the onset of the next menstruation, we followed up with women who had not menstruated in the last 5 days of the diary, until the next menstrual onset for up to 40 days.

Metadata

Description

Dataset name: s5_hadmenstruation

The dataset has N=442 rows and 3 columns. 442 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
created_date
menstrual_onset_date_inferred

#Variables

created_date

user first opened survey

Distribution

## 153  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
created_date	user first opened survey	Date	0	1	153	2016-07-17	2016-12-31	2017-04-24

menstrual_onset_date_inferred

Bitte geben Sie das genaue Datum des ersten Tages Ihrer letzten Menstruationsblutung an. Schauen Sie dazu ggf. in Ihrem Kalender nach.

Distribution

## 171  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	label	type	type_options	data_type	optional	showif	item_order	n_missing	complete_rate	n_unique	min	median	max
menstrual_onset_date_inferred	Bitte geben Sie das genaue Datum des ersten Tages Ihrer letzten Menstruationsblutung an. Schauen Sie dazu ggf. in Ihrem Kalender nach.	date	-2months,today	Date	0	had_menstrual_bleeding == 1	3	0	1	171	2016-07-08	2016-12-28	2017-04-20

Item

Item options
type	type_options	name	label	optional	showif	item_order
date	-2months,today	last_menstrual_onset_date	Bitte geben Sie das genaue Datum des ersten Tages Ihrer letzten Menstruationsblutung an. Schauen Sie dazu ggf. in Ihrem Kalender nach.	0	had_menstrual_bleeding == 1	3

Value labels

Response choices
name	value

Missingness report

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "s5_hadmenstruation",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=442 rows and 3 columns.\n442 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name                          |label                                                                                                                                  | n_missing|\n|:-----------------------------|:--------------------------------------------------------------------------------------------------------------------------------------|---------:|\n|session                       |NA                                                                                                                                     |         0|\n|created_date                  |user first opened survey                                                                                                               |         0|\n|menstrual_onset_date_inferred |Bitte geben Sie das genaue Datum des ersten Tages Ihrer letzten Menstruationsblutung an. Schauen Sie dazu ggf. in Ihrem Kalender nach. |         0|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "created_date", "menstrual_onset_date_inferred"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created_date",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "menstrual_onset_date_inferred",
      "description": "Bitte geben Sie das genaue Datum des ersten Tages Ihrer letzten Menstruationsblutung an. Schauen Sie dazu ggf. in Ihrem Kalender nach.",
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    }
  ]
}`

Lab Study

A subset of the diary participants also participated in a lab study, in which hormones where collected. Participation dates were intended to overlap, but scheduling did not always permit this.

Metadata

Description

Dataset name: lab

The dataset has N=552 rows and 53 columns. 0 rows have no missing values on any column.

Metadata for search engines

Date published: 2020-06-11

x
session
short
VPN-CODE
Tagebuchcode
VPN-Zahl
created_date
Uhrzeit
Date LH surge
exclude_luteal_too_long
Menstrual Onset
Versuchsleiterin1
Versuchsleiterin2
Derzeitige Schwellungen
Session Nr.
Zyklusphase
Ratings Körper
Ratings Stimmen
Ratings Verhalten
Age
Relationship_status
Relationship_Duration
Cortisol nmol/l
Testosterone pg/ml
Progesterone pg/ml
Estradiol pg/ml
IBL_Estradiol pg/ml
IBL_E/P
self.reported.stress
Lungenvolumen 1. Messung
Lungenvolumen 2. Messung
Lungenvolumen 3. Messung
MEAN Lungenvolumen
Handgriffstärke Links 1. Messung
Handgriffstärke Links 2. Messung
Handgriffstärke Links 3. Messung
MEAN Handgriffstärke Links
Handgriffstärke rechts 1. Messung
Handgriffstärke rechts 2. Messung
Handgriffstärke rechts 3. Messung
MEAN Handgriffstärke rechts
Oberkörperstärke 1. Messung
Oberkörperstärke 2. Messung
Oberkörperstärke 3. Messung
MEAN Oberkörperstärke
Größe 1. Messung
Größe 2. Messung
MEAN Größe
Gewicht 1. Messung
Gewicht 2. Messung
Gewicht 3. Messung
MEAN Gewicht
BMI
Sonstiges

#Variables

short

Distribution

Distribution of values for short

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
short	character	0	1	138	0	7	7	0	NA

VPN-CODE

Distribution

Distribution of values for VPN-CODE

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
VPN-CODE	character	0	1	140	0	9	11	0	NA

Tagebuchcode

Distribution

Distribution of values for Tagebuchcode

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
Tagebuchcode	character	0	1	198	0	64	65	0	NA

VPN-Zahl

Distribution

Distribution of values for VPN-Zahl

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
VPN-Zahl	numeric	0	1	100	192	279	191.3	50.9	▆▇▇▇▇	NA

created_date

Distribution

## 168  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
created_date	Date	0	1	168	2016-03-06	2016-10-21	2017-03-15	NA

Uhrzeit

Distribution

## 34  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
Uhrzeit	POSIXct	0	1	34	1899-12-31 09:00:00	1899-12-31 13:22:30	1899-12-31 22:00:00	NA

Date LH surge

Distribution

## 157  unique, categorical values, so not shown.

305 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
Date LH surge	Date	305	0.4475	157	2016-05-07	2016-10-21	2017-03-16	NA

exclude_luteal_too_long

Distribution

Distribution of values for exclude_luteal_too_long

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
exclude_luteal_too_long	numeric	0	1	0	0	1	0.0616	0.2406	▇▁▁▁▁	NA

Menstrual Onset

Distribution

## 198  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	min	median	max	label
Menstrual Onset	POSIXct	0	1	198	2016-05-13	2016-11-05	2017-03-27	NA

Versuchsleiterin1

Distribution

Distribution of values for Versuchsleiterin1

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Versuchsleiterin1	numeric	0	1	1	2	5	2.217	1.081	▇▇▅▂▁	NA

Versuchsleiterin2

Distribution

Distribution of values for Versuchsleiterin2

489 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Versuchsleiterin2	numeric	489	0.1141	1	4	5	3.365	1.021	▁▅▃▇▂	NA

Derzeitige Schwellungen

Distribution

Distribution of values for Derzeitige Schwellungen

538 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
Derzeitige Schwellungen	character	538	0.0254	13	0	10	49	0	NA

Session Nr.

Distribution

Distribution of values for Session Nr.

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Session Nr.	numeric	0	1	1	2.5	4	2.502	1.117	▇▇▁▇▇	NA

Zyklusphase

Distribution

Distribution of values for Zyklusphase

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Zyklusphase	numeric	0	1	1	1.5	2	1.5	0.5005	▇▁▁▁▇	NA

Ratings Körper

Distribution

Distribution of values for Ratings Körper

8 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Ratings Körper	numeric	8	0.9855	1	2	3	2.018	0.7381	▅▁▇▁▅	NA

Ratings Stimmen

Distribution

Distribution of values for Ratings Stimmen

9 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Ratings Stimmen	numeric	9	0.9837	1	2	3	2.044	0.8834	▇▁▅▁▇	NA

Ratings Verhalten

Distribution

Distribution of values for Ratings Verhalten

8 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Ratings Verhalten	numeric	8	0.9855	1	2	3	1.934	0.8183	▇▁▇▁▆	NA

Age

Distribution

Distribution of values for Age

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Age	numeric	0	1	18	23	35	23.25	3.433	▇▇▅▂▁	NA

Relationship_status

Distribution

Distribution of values for Relationship_status

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Relationship_status	numeric	0	1	1	1	5	1.897	1.046	▇▁▅▁▁	NA

Relationship_Duration

Distribution

Distribution of values for Relationship_Duration

298 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Relationship_Duration	numeric	298	0.4601	0	20	143	31.61	33.29	▇▃▂▁▁	NA

Cortisol nmol/l

Distribution

Distribution of values for Cortisol nmol/l

2 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Cortisol nmol/l	numeric	2	0.9964	0.062	3	34	3.918	3.497	▇▁▁▁▁	NA

Testosterone pg/ml

Distribution

Distribution of values for Testosterone pg/ml

18 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Testosterone pg/ml	numeric	18	0.9674	1.4	7.2	302	9.201	16.95	▇▁▁▁▁	NA

Progesterone pg/ml

Distribution

Distribution of values for Progesterone pg/ml

43 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Progesterone pg/ml	numeric	43	0.9221	0.26	14	281	49.37	65.58	▇▂▁▁▁	NA

Estradiol pg/ml

Distribution

Distribution of values for Estradiol pg/ml

428 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Estradiol pg/ml	numeric	428	0.2246	2.1	8.1	260	15.6	31.48	▇▁▁▁▁	NA

IBL_Estradiol pg/ml

Distribution

Distribution of values for IBL_Estradiol pg/ml

30 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
IBL_Estradiol pg/ml	numeric	30	0.9457	0.15	5	31	5.928	3.981	▇▃▁▁▁	NA

IBL_E/P

Distribution

Distribution of values for IBL_E/P

70 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
IBL_E/P	numeric	70	0.8732	0.0018	0.33	28	0.8819	1.814	▇▁▁▁▁	NA

self.reported.stress

Distribution

Distribution of values for self.reported.stress

234 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
self.reported.stress	numeric	234	0.5761	0	2	4	1.953	1.096	▃▆▇▇▂	NA

Lungenvolumen 1. Messung

Distribution

Distribution of values for Lungenvolumen 1. Messung

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Lungenvolumen 1. Messung	numeric	0	1	0.66	2.9	4.3	2.804	0.6155	▁▂▆▇▂	NA

Lungenvolumen 2. Messung

Distribution

Distribution of values for Lungenvolumen 2. Messung

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Lungenvolumen 2. Messung	numeric	0	1	0.33	2.9	4.4	2.833	0.601	▁▂▅▇▂	NA

Lungenvolumen 3. Messung

Distribution

Distribution of values for Lungenvolumen 3. Messung

1 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Lungenvolumen 3. Messung	numeric	1	0.9982	0.56	2.9	4.2	2.863	0.6042	▁▂▅▇▂	NA

MEAN Lungenvolumen

Distribution

Distribution of values for MEAN Lungenvolumen

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Lungenvolumen	numeric	0	1	0.79	2.9	4.1	2.833	0.5762	▁▂▅▇▂	NA

Handgriffstärke Links 1. Messung

Distribution

Distribution of values for Handgriffstärke Links 1. Messung

18 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke Links 1. Messung	numeric	18	0.9674	12	26	47	26.43	5.79	▂▇▇▂▁	NA

Handgriffstärke Links 2. Messung

Distribution

Distribution of values for Handgriffstärke Links 2. Messung

4 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke Links 2. Messung	numeric	4	0.9928	11	24	46	25.05	5.889	▂▇▆▂▁	NA

Handgriffstärke Links 3. Messung

Distribution

Distribution of values for Handgriffstärke Links 3. Messung

2 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke Links 3. Messung	numeric	2	0.9964	10	24	46	24.36	5.952	▂▇▆▂▁	NA

MEAN Handgriffstärke Links

Distribution

Distribution of values for MEAN Handgriffstärke Links

1 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Handgriffstärke Links	numeric	1	0.9982	12	25	46	25.29	5.658	▂▇▆▂▁	NA

Handgriffstärke rechts 1. Messung

Distribution

Distribution of values for Handgriffstärke rechts 1. Messung

75 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke rechts 1. Messung	numeric	75	0.8641	15	29	50	28.97	6.309	▃▇▇▂▁	NA

Handgriffstärke rechts 2. Messung

Distribution

Distribution of values for Handgriffstärke rechts 2. Messung

6 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke rechts 2. Messung	numeric	6	0.9891	12	28	55	27.62	6.122	▂▇▅▁▁	NA

Handgriffstärke rechts 3. Messung

Distribution

Distribution of values for Handgriffstärke rechts 3. Messung

6 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Handgriffstärke rechts 3. Messung	numeric	6	0.9891	11	26	48	26.77	6.108	▂▆▇▂▁	NA

MEAN Handgriffstärke rechts

Distribution

Distribution of values for MEAN Handgriffstärke rechts

4 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Handgriffstärke rechts	numeric	4	0.9928	13	28	49	27.74	5.801	▂▇▇▂▁	NA

Oberkörperstärke 1. Messung

Distribution

Distribution of values for Oberkörperstärke 1. Messung

48 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Oberkörperstärke 1. Messung	numeric	48	0.913	4	19	40	20.13	6.754	▂▇▇▃▁	NA

Oberkörperstärke 2. Messung

Distribution

Distribution of values for Oberkörperstärke 2. Messung

2 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Oberkörperstärke 2. Messung	numeric	2	0.9964	4	19	49	18.98	6.618	▃▇▅▁▁	NA

Oberkörperstärke 3. Messung

Distribution

Distribution of values for Oberkörperstärke 3. Messung

2 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Oberkörperstärke 3. Messung	numeric	2	0.9964	4	18	40	19.04	6.646	▃▇▇▃▁	NA

MEAN Oberkörperstärke

Distribution

Distribution of values for MEAN Oberkörperstärke

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Oberkörperstärke	numeric	0	1	4.7	19	43	19.35	6.203	▃▇▇▂▁	NA

Größe 1. Messung

Distribution

Distribution of values for Größe 1. Messung

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Größe 1. Messung	numeric	0	1	145	171	187	170	6.489	▁▂▇▇▂	NA

Größe 2. Messung

Distribution

Distribution of values for Größe 2. Messung

11 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Größe 2. Messung	numeric	11	0.9801	146	171	187	170	6.412	▁▂▇▇▂	NA

MEAN Größe

Distribution

Distribution of values for MEAN Größe

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Größe	numeric	0	1	68	171	187	169.8	7.81	▁▁▁▁▇	NA

Gewicht 1. Messung

Distribution

Distribution of values for Gewicht 1. Messung

5 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Gewicht 1. Messung	numeric	5	0.9909	42	64	116	65.22	11.45	▃▇▂▁▁	NA

Gewicht 2. Messung

Distribution

Distribution of values for Gewicht 2. Messung

7 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Gewicht 2. Messung	numeric	7	0.9873	42	64	116	65.17	11.45	▃▇▂▁▁	NA

Gewicht 3. Messung

Distribution

Distribution of values for Gewicht 3. Messung

143 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
Gewicht 3. Messung	numeric	143	0.7409	42	64	114	65.09	11.47	▃▇▃▁▁	NA

MEAN Gewicht

Distribution

Distribution of values for MEAN Gewicht

5 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
MEAN Gewicht	numeric	5	0.9909	42	64	116	65.22	11.45	▃▇▂▁▁	NA

BMI

Distribution

Distribution of values for BMI

5 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
BMI	numeric	5	0.9909	16	22	148	22.75	6.378	▇▁▁▁▁	NA

Sonstiges

Distribution

Distribution of values for Sonstiges

535 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
Sonstiges	character	535	0.0308	17	0	11	92	0	NA

Missingness report

## # A tibble: 21 x 36
##    description `Lungenvolumen … `MEAN Handgriff… `Cortisol nmol/… `Handgriffstärk… `Oberkörperstär…
##    <chr>                  <dbl>            <dbl>            <dbl>            <dbl>            <dbl>
##  1 Missing va…                1                1                2                2                2
##  2 Missing va…                1                1                1                1                1
##  3 Missing va…                1                1                1                1                1
##  4 Missing va…                1                1                1                1                1
##  5 Missing va…                1                1                1                1                1
##  6 Missing va…                1                1                1                1                1
##  7 Missing va…                1                1                1                1                1
##  8 Missing va…                1                1                1                1                1
##  9 Missing va…                1                1                1                1                1
## 10 Missing va…                1                1                1                1                1
## # … with 11 more rows, and 30 more variables: `Oberkörperstärke 3. Messung` <dbl>, `Handgriffstärke Links 2.
## #   Messung` <dbl>, `MEAN Handgriffstärke rechts` <dbl>, `Gewicht 1. Messung` <dbl>, `MEAN Gewicht` <dbl>,
## #   BMI <dbl>, `Handgriffstärke rechts 2. Messung` <dbl>, `Handgriffstärke rechts 3. Messung` <dbl>, `Gewicht
## #   2. Messung` <dbl>, `Ratings Körper` <dbl>, `Ratings Verhalten` <dbl>, `Ratings Stimmen` <dbl>, `Größe 2.
## #   Messung` <dbl>, `Testosterone pg/ml` <dbl>, `Handgriffstärke Links 1. Messung` <dbl>, `IBL_Estradiol
## #   pg/ml` <dbl>, `Progesterone pg/ml` <dbl>, `Oberkörperstärke 1. Messung` <dbl>, `IBL_E/P` <dbl>,
## #   `Handgriffstärke rechts 1. Messung` <dbl>, `Gewicht 3. Messung` <dbl>, self.reported.stress <dbl>,
## #   Relationship_Duration <dbl>, `Date LH surge` <dbl>, `Estradiol pg/ml` <dbl>, Versuchsleiterin2 <dbl>,
## #   Sonstiges <dbl>, `Derzeitige Schwellungen` <dbl>, var_miss <dbl>, n_miss <dbl>

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "lab",
  "datePublished": "2020-06-11",
  "description": "The dataset has N=552 rows and 53 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name                              |label | n_missing|\n|:---------------------------------|:-----|---------:|\n|session                           |NA    |         0|\n|short                             |NA    |         0|\n|VPN-CODE                          |NA    |         0|\n|Tagebuchcode                      |NA    |         0|\n|VPN-Zahl                          |NA    |         0|\n|created_date                      |NA    |         0|\n|Uhrzeit                           |NA    |         0|\n|Date LH surge                     |NA    |       305|\n|exclude_luteal_too_long           |NA    |         0|\n|Menstrual Onset                   |NA    |         0|\n|Versuchsleiterin1                 |NA    |         0|\n|Versuchsleiterin2                 |NA    |       489|\n|Derzeitige Schwellungen           |NA    |       538|\n|Session Nr.                       |NA    |         0|\n|Zyklusphase                       |NA    |         0|\n|Ratings Körper                    |NA    |         8|\n|Ratings Stimmen                   |NA    |         9|\n|Ratings Verhalten                 |NA    |         8|\n|Age                               |NA    |         0|\n|Relationship_status               |NA    |         0|\n|Relationship_Duration             |NA    |       298|\n|Cortisol nmol/l                   |NA    |         2|\n|Testosterone pg/ml                |NA    |        18|\n|Progesterone pg/ml                |NA    |        43|\n|Estradiol pg/ml                   |NA    |       428|\n|IBL_Estradiol pg/ml               |NA    |        30|\n|IBL_E/P                           |NA    |        70|\n|self.reported.stress              |NA    |       234|\n|Lungenvolumen 1. Messung          |NA    |         0|\n|Lungenvolumen 2. Messung          |NA    |         0|\n|Lungenvolumen 3. Messung          |NA    |         1|\n|MEAN Lungenvolumen                |NA    |         0|\n|Handgriffstärke Links 1. Messung  |NA    |        18|\n|Handgriffstärke Links 2. Messung  |NA    |         4|\n|Handgriffstärke Links 3. Messung  |NA    |         2|\n|MEAN Handgriffstärke Links        |NA    |         1|\n|Handgriffstärke rechts 1. Messung |NA    |        75|\n|Handgriffstärke rechts 2. Messung |NA    |         6|\n|Handgriffstärke rechts 3. Messung |NA    |         6|\n|MEAN Handgriffstärke rechts       |NA    |         4|\n|Oberkörperstärke 1. Messung       |NA    |        48|\n|Oberkörperstärke 2. Messung       |NA    |         2|\n|Oberkörperstärke 3. Messung       |NA    |         2|\n|MEAN Oberkörperstärke             |NA    |         0|\n|Größe 1. Messung                  |NA    |         0|\n|Größe 2. Messung                  |NA    |        11|\n|MEAN Größe                        |NA    |         0|\n|Gewicht 1. Messung                |NA    |         5|\n|Gewicht 2. Messung                |NA    |         7|\n|Gewicht 3. Messung                |NA    |       143|\n|MEAN Gewicht                      |NA    |         5|\n|BMI                               |NA    |         5|\n|Sonstiges                         |NA    |       535|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.3).",
  "keywords": ["session", "short", "VPN-CODE", "Tagebuchcode", "VPN-Zahl", "created_date", "Uhrzeit", "Date LH surge", "exclude_luteal_too_long", "Menstrual Onset", "Versuchsleiterin1", "Versuchsleiterin2", "Derzeitige Schwellungen", "Session Nr.", "Zyklusphase", "Ratings Körper", "Ratings Stimmen", "Ratings Verhalten", "Age", "Relationship_status", "Relationship_Duration", "Cortisol nmol/l", "Testosterone pg/ml", "Progesterone pg/ml", "Estradiol pg/ml", "IBL_Estradiol pg/ml", "IBL_E/P", "self.reported.stress", "Lungenvolumen 1. Messung", "Lungenvolumen 2. Messung", "Lungenvolumen 3. Messung", "MEAN Lungenvolumen", "Handgriffstärke Links 1. Messung", "Handgriffstärke Links 2. Messung", "Handgriffstärke Links 3. Messung", "MEAN Handgriffstärke Links", "Handgriffstärke rechts 1. Messung", "Handgriffstärke rechts 2. Messung", "Handgriffstärke rechts 3. Messung", "MEAN Handgriffstärke rechts", "Oberkörperstärke 1. Messung", "Oberkörperstärke 2. Messung", "Oberkörperstärke 3. Messung", "MEAN Oberkörperstärke", "Größe 1. Messung", "Größe 2. Messung", "MEAN Größe", "Gewicht 1. Messung", "Gewicht 2. Messung", "Gewicht 3. Messung", "MEAN Gewicht", "BMI", "Sonstiges"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "short",
      "@type": "propertyValue"
    },
    {
      "name": "VPN-CODE",
      "@type": "propertyValue"
    },
    {
      "name": "Tagebuchcode",
      "@type": "propertyValue"
    },
    {
      "name": "VPN-Zahl",
      "@type": "propertyValue"
    },
    {
      "name": "created_date",
      "@type": "propertyValue"
    },
    {
      "name": "Uhrzeit",
      "@type": "propertyValue"
    },
    {
      "name": "Date LH surge",
      "@type": "propertyValue"
    },
    {
      "name": "exclude_luteal_too_long",
      "@type": "propertyValue"
    },
    {
      "name": "Menstrual Onset",
      "@type": "propertyValue"
    },
    {
      "name": "Versuchsleiterin1",
      "@type": "propertyValue"
    },
    {
      "name": "Versuchsleiterin2",
      "@type": "propertyValue"
    },
    {
      "name": "Derzeitige Schwellungen",
      "@type": "propertyValue"
    },
    {
      "name": "Session Nr.",
      "@type": "propertyValue"
    },
    {
      "name": "Zyklusphase",
      "@type": "propertyValue"
    },
    {
      "name": "Ratings Körper",
      "@type": "propertyValue"
    },
    {
      "name": "Ratings Stimmen",
      "@type": "propertyValue"
    },
    {
      "name": "Ratings Verhalten",
      "@type": "propertyValue"
    },
    {
      "name": "Age",
      "@type": "propertyValue"
    },
    {
      "name": "Relationship_status",
      "@type": "propertyValue"
    },
    {
      "name": "Relationship_Duration",
      "@type": "propertyValue"
    },
    {
      "name": "Cortisol nmol/l",
      "@type": "propertyValue"
    },
    {
      "name": "Testosterone pg/ml",
      "@type": "propertyValue"
    },
    {
      "name": "Progesterone pg/ml",
      "@type": "propertyValue"
    },
    {
      "name": "Estradiol pg/ml",
      "@type": "propertyValue"
    },
    {
      "name": "IBL_Estradiol pg/ml",
      "@type": "propertyValue"
    },
    {
      "name": "IBL_E/P",
      "@type": "propertyValue"
    },
    {
      "name": "self.reported.stress",
      "@type": "propertyValue"
    },
    {
      "name": "Lungenvolumen 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Lungenvolumen 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Lungenvolumen 3. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Lungenvolumen",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke Links 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke Links 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke Links 3. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Handgriffstärke Links",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke rechts 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke rechts 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Handgriffstärke rechts 3. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Handgriffstärke rechts",
      "@type": "propertyValue"
    },
    {
      "name": "Oberkörperstärke 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Oberkörperstärke 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Oberkörperstärke 3. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Oberkörperstärke",
      "@type": "propertyValue"
    },
    {
      "name": "Größe 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Größe 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Größe",
      "@type": "propertyValue"
    },
    {
      "name": "Gewicht 1. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Gewicht 2. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "Gewicht 3. Messung",
      "@type": "propertyValue"
    },
    {
      "name": "MEAN Gewicht",
      "@type": "propertyValue"
    },
    {
      "name": "BMI",
      "@type": "propertyValue"
    },
    {
      "name": "Sonstiges",
      "@type": "propertyValue"
    }
  ]
}`

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

Codebook GOCD2

Demographics

Metadata

Description

Survey overview

info_study

Distribution

Summary statistics

Item

Value labels

lab_code

Distribution

Summary statistics

Item

Value labels

age

Distribution

Summary statistics

Item

Value labels

gender

Distribution

Summary statistics

Item

Value labels

gender_other

Distribution

Summary statistics

Item

Value labels

education_years

Distribution

Summary statistics

Item

Value labels

education_level

Distribution

Summary statistics

Item

Value labels

education_level_special

Distribution

Summary statistics

Item

Value labels

occupational_status

Distribution

Summary statistics

Item

Value labels

occupation

Distribution

Summary statistics

Item

Value labels

net_income

Distribution

Summary statistics

Item

Value labels

study_major

Distribution

Summary statistics

Item

Value labels

postal_code

Distribution

Summary statistics

Item

Value labels

religion

Distribution

Summary statistics

Item

Value labels

religiosity

Distribution

Summary statistics

Item

Value labels