Do voices carry valid information about a speaker’s personality?

Results

• Integration/Aggregation of individual datasets.
• Codebook: The codebook contains metadata, means, missingness, correlations, sex differences, age trends, and further information on all variables in the study. We also provide a codebook with unstandardised variables.
• Preregistered tests for preregistered outcomes (dominance, extraversion, agreeableness, SOI behavior)
• Exploratory analyses for additional outcomes.
• Robustness checks for the preregistered outcomes.

Voice pitch and formants

To hear different voice pitches and formants, click the initials of the authors of our study below. You’ll hear each of us read part of the rainbow passage. The big, clickable dots show the authors; they are superimposed on the data used in this study (men coloured in black, women coloured in blue).

The rainbow passage

When the sunlight strikes raindrops in the air, they act like a prism and form a rainbow. The rainbow is a division of white light into many beautiful colors. These take the shape of a long round arch, with its path high above, and its two ends apparently beyond the horizon. There is, according to legend, a boiling pot of gold at one end. People look but no one ever finds it. When a man looks for something beyond his reach, his friends say he is looking for the pot of gold at the end of the rainbow.

Reproducibility

This repository uses the renv package to make it easier to rerun analyses using the same setup and package versions that were used to create them.

Here’s a classical session info.

library(tidyverse)
library(knitr)
library(brms)

## Loading required package: Rcpp

## Loading 'brms' package (version 2.15.0). Useful instructions
## can be found by typing help('brms'). A more detailed introduction
## to the package is available through vignette('brms_overview').

## 
## Attaching package: 'brms'

## The following object is masked from 'package:stats':
## 
##     ar

library(sjPlot)
library(bayestestR)
library(labelled)
library(cowplot)

## 
## ********************************************************

## Note: As of version 1.0.0, cowplot does not change the

##   default ggplot2 theme anymore. To recover the previous

##   behavior, execute:
##   theme_set(theme_cowplot())

## ********************************************************

## 
## Attaching package: 'cowplot'

## The following objects are masked from 'package:sjPlot':
## 
##     plot_grid, save_plot

library(labelled)
library(codebook)

## 
## Attaching package: 'codebook'

## The following object is masked from 'package:labelled':
## 
##     to_factor

library(ggstatsplot)

## In case you would like cite this package, cite it as:
##      Patil, I. (2018). ggstatsplot: "ggplot2" Based Plots with Statistical Details. CRAN.
##      Retrieved from https://cran.r-project.org/web/packages/ggstatsplot/index.html

sessionInfo()

## R version 4.0.5 (2021-03-31)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices datasets  utils     methods   base     
## 
## other attached packages:
##  [1] ggstatsplot_0.7.1 codebook_0.9.3    cowplot_1.0.0     labelled_2.5.0   
##  [5] bayestestR_0.9.0  sjPlot_2.8.4      brms_2.15.0       Rcpp_1.0.4.6     
##  [9] knitr_1.29        forcats_0.5.0     stringr_1.4.0     dplyr_1.0.0      
## [13] purrr_0.3.4       readr_1.3.1       tidyr_1.1.0       tibble_3.0.1     
## [17] ggplot2_3.3.3     tidyverse_1.3.0   r2d3_0.2.3       
## 
## loaded via a namespace (and not attached):
##   [1] tidyselect_1.1.0          lme4_1.1-23              
##   [3] htmlwidgets_1.5.1         grid_4.0.5               
##   [5] gmp_0.6-0                 munsell_0.5.0            
##   [7] codetools_0.2-16          effectsize_0.4.4-1       
##   [9] statmod_1.4.34            DT_0.14                  
##  [11] miniUI_0.1.1.1            withr_2.2.0              
##  [13] Brobdingnag_1.2-6         colorspace_1.4-1         
##  [15] rstudioapi_0.11           stats4_4.0.5             
##  [17] ipmisc_6.0.0              ggsignif_0.6.1           
##  [19] bayesplot_1.7.2           emmeans_1.4.7            
##  [21] rstan_2.21.1              bridgesampling_1.0-0     
##  [23] coda_0.19-3               vctrs_0.3.1              
##  [25] generics_0.0.2            TH.data_1.0-10           
##  [27] xfun_0.15                 BWStest_0.2.2            
##  [29] R6_2.4.1                  markdown_1.1             
##  [31] BayesFactor_0.9.12-4.2    gamm4_0.2-6              
##  [33] projpred_2.0.2            reshape_0.8.8            
##  [35] assertthat_0.2.1          promises_1.1.1           
##  [37] scales_1.1.1              multcomp_1.4-13          
##  [39] ggExtra_0.9               gtable_0.3.0             
##  [41] multcompView_0.1-8        processx_3.5.1           
##  [43] sandwich_2.5-1            rlang_0.4.10             
##  [45] MatrixModels_0.4-1        zeallot_0.1.0            
##  [47] PMCMRplus_1.4.4           splines_4.0.5            
##  [49] broom_0.5.6               inline_0.3.15            
##  [51] yaml_2.2.1                reshape2_1.4.4           
##  [53] abind_1.4-5               modelr_0.1.8             
##  [55] threejs_0.3.3             crosstalk_1.1.0.1        
##  [57] backports_1.1.8           httpuv_1.5.4             
##  [59] rsconnect_0.8.16          tools_4.0.5              
##  [61] ellipsis_0.3.1            WRS2_1.1-1               
##  [63] ggridges_0.5.2            plyr_1.8.6               
##  [65] base64enc_0.1-3           ps_1.3.3                 
##  [67] prettyunits_1.1.1         pbapply_1.4-2            
##  [69] correlation_0.6.1         zoo_1.8-8                
##  [71] haven_2.3.1               ggrepel_0.8.2            
##  [73] fs_1.4.1                  magrittr_1.5             
##  [75] data.table_1.12.8         openxlsx_4.1.5           
##  [77] colourpicker_1.0          reprex_0.3.0             
##  [79] mvtnorm_1.1-1             sjmisc_2.8.5             
##  [81] matrixStats_0.56.0        patchwork_1.1.1          
##  [83] hms_0.5.3                 shinyjs_1.1              
##  [85] mime_0.9                  evaluate_0.14            
##  [87] xtable_1.8-4              shinystan_2.5.0          
##  [89] rio_0.5.26                sjstats_0.18.0           
##  [91] pairwiseComparisons_3.1.3 readxl_1.3.1             
##  [93] gridExtra_2.3             ggeffects_0.15.0         
##  [95] rstantools_2.1.1          compiler_4.0.5           
##  [97] V8_3.2.0                  crayon_1.3.4             
##  [99] minqa_1.2.4               StanHeaders_2.21.0-5     
## [101] htmltools_0.5.0           mc2d_0.1-18              
## [103] mgcv_1.8-31               later_1.1.0.1            
## [105] RcppParallel_5.0.2        lubridate_1.7.9          
## [107] DBI_1.1.0                 SuppDists_1.1-9.5        
## [109] kSamples_1.2-9            sjlabelled_1.1.6         
## [111] dbplyr_1.4.4              MASS_7.3-51.6            
## [113] boot_1.3-25               Matrix_1.2-18            
## [115] cli_2.0.2                 parallel_4.0.5           
## [117] insight_0.13.2            igraph_1.2.5             
## [119] pkgconfig_2.0.3           statsExpressions_1.0.0   
## [121] foreign_0.8-81            paletteer_1.2.0          
## [123] xml2_1.3.2                dygraphs_1.1.1.6         
## [125] ggcorrplot_0.1.3          estimability_1.3         
## [127] rvest_0.3.5               callr_3.4.3              
## [129] digest_0.6.25             parameters_0.13.0        
## [131] rmarkdown_2.7             cellranger_1.1.0         
## [133] curl_4.3                  shiny_1.5.0              
## [135] gtools_3.8.2              nloptr_1.2.2.1           
## [137] lifecycle_0.2.0           nlme_3.1-148             
## [139] jsonlite_1.7.0            fansi_0.4.1              
## [141] pillar_1.4.4              lattice_0.20-41          
## [143] loo_2.4.1                 fastmap_1.0.1            
## [145] httr_1.4.1                pkgbuild_1.0.8           
## [147] survival_3.2-3            glue_1.4.1               
## [149] xts_0.12-0                zip_2.0.4                
## [151] shinythemes_1.1.2         stringi_1.4.6            
## [153] performance_0.4.7         rematch2_2.1.2           
## [155] blob_1.2.1                memoise_1.1.0            
## [157] renv_0.11.0               Rmpfr_0.8-1

Here’s our renv lockfile.

cat(readLines("renv.lock"), sep = "\n")

## {
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##     "Version": "4.0.1",
##     "Repositories": [
##       {
##         "Name": "CRAN",
##         "URL": "https://cran.rstudio.com"
##       }
##     ]
##   },
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##       "Repository": "CRAN",
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##     },
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##       "Repository": "CRAN",
##       "Hash": "8f9ce74c6417d61f0782cbae5fd2b7b0"
##     },
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##       "Package": "BWStest",
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##       "Source": "Repository",
##       "Repository": "CRAN",
##       "Hash": "c8727f10292b1913b40c05dd659c5f08"
##     },
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