Pass a data frame to this function to make a codebook for that dataset.
If the dataset has metadata (attributes) set on its variables, these will be
used to make the codebook more informative. Examples are item, value, and
missing labels.
Data frames imported via haven::read_dta(), haven::read_sav(), or from
formr.org will have these attributes in the right format.
By calling this function inside a knitr code chunk, the
codebook will become part of the document you are generating.
Usage
codebook(
results,
reliabilities = NULL,
survey_repetition = c("auto", "single", "repeated_once", "repeated_many"),
detailed_variables = TRUE,
detailed_scales = TRUE,
survey_overview = TRUE,
missingness_report = TRUE,
metadata_table = TRUE,
metadata_json = TRUE,
indent = "#"
)Arguments
- results
a data frame, ideally with attributes set on variables
- reliabilities
a named list with one entry per scale and one or several printable reliability computations for this scale. if NULL, computed on-the-fly using compute_reliabilities
- survey_repetition
defaults to "auto" which is to try to determine the level of repetition from the "session" and "created" variables. Other values are: single, repeated_once, repeated_many
- detailed_variables
whether to print a graph and summary for each variable
- detailed_scales
whether to print a graph and summary for each scale
- survey_overview
whether to print an overview of survey entries, durations (depends on presence of columns session, created, modified, ended, expired)
- missingness_report
whether to print a missingness report. Turn off if this gets too complicated and you need a custom solution (e.g. in case of random missings).
- metadata_table
whether to print a metadata table/tabular codebook.
- metadata_json
whether to include machine-readable metadata as JSON-LD (not visible)
- indent
add # to this to make the headings in the components lower-level. defaults to beginning at h2