bramzandbelt / irmass

Independent race model analysis of selective stopping

irmass - Research compendium for the report on independent race model analysis of selective stopping by Zandbelt & Van den Bosch

Compendium DOI

DOI: 10.5281/zenodo.3257329

The files at the URL above will generate the results as found in the preprint. The files hosted at https://github.com/bramzandbelt/irmass are the development versions and may have changed since the preprint was published.

Author of this repository

Bram Zandbelt ([email protected])

Published in:

TBA

Overview of contents

The packagae irmass is one of two research compendia of the research project Cognitive and Neurobiological Mechanisms of Selective Stopping by Bram Zandbelt and Ruben van den Bosch (the other research compendium, cnmss, can be found here). This project was conducted at the Donders Institute, Radboud University, Nijmegen, the Netherlands, and registered at the Donders Centre for Cognitive Neuroimaging under project number 3017031.05 (DCCN PI: Roshan Cools).

This research compendium contains all data, code, and text associated with the above-mentioned publication and is organized as follows (showing directories in a tree-like format with a maximum depth of two levels):

.
├── R
├── analysis
│   ├── bash
│   └── notebooks_and_scripts
├── data
│   └── derivatives
├── documents
│   ├── content
│   └── context
├── figures
│   ├── 01_preprocess_log_files
│   ├── 02_assess_task_performance_criteria
│   ├── 03_individual_analysis_effect_ssd_on_prob_responding_given_stopsignal
│   ├── 04_individual_analysis_rt_difference_nosignal_stoprespond
│   ├── 05_individual_analysis_effect_ssd_on_stoprespond_rt
│   ├── 07_group_analysis_rt_difference_nosignal_stoprespond
│   ├── 08_group_analysis_effect_ssd_on_stoprespond_rt
│   └── 09_exploration_support_for_hypotheses_under_different_bayes_factor_criteria
├── man
├── packrat
│   ├── lib
│   ├── lib-R
│   ├── lib-ext
│   └── src
└── reports

The R/ directory contains:

• R code specific to the present project; functions are organized into files (e.g. functions for plotting are in plot_functions.R).

The analysis/ directory contains:

• R Markdown notebooks implementing the analyses (notebooks_and_scripts/ directory), numbered in the order in which they should be run;
• shell scripts running the R Markdown notebooks with appropriate parameters, if any (bash/ directory).

The data/ directory contains:

• the data derived from the raw data (derivatives/ directory), organized by notebook name.
  • for meaning of output variables, see the codebooks of the notebook 01_preprocess_log_files (documents/content/01_preprocess_log_files/), the notebooks (analysis/*.Rmd), and static reports (reports/)
• the simulated performance data (simulations/ directory)

N.B. The raw data is not shared, because it contains information about date and time on which the session took place, potentially allowing for identification of participants (e.g. by participants themselves). However, the raw data are archived at the Donders Center for Cognitive Neuroimaging under project number 3017031.05

The documents/ directory contains:

• documents describing the content of the experimental data (content/ directory), such as codebooks;
• documents describing the context of the data (context/ directory), such as ethics documents, preregistration, and task instructions;
• documents related to the report of this research project (manuscript/ directory).

The figures/ directory contains:

• visualizations of descriptive and inferential statistics, organized by notebook name.

The man/ directory contains:

• documentation of objects inside the package, generated by roxygen2.

The packrat/ directory contains:

• R packages the research compendium depends on; for more info see https://rstudio.github.io/packrat/.

The reports/ directory contains:

• static HTML versions of the knitted R Markdown notebooks, organized by notebook name.

Finally, this research compendium is associated with a number of online objects, including:

object	archived version	development version
preregistration	https://osf.io/mq64z/	NA
stimulus presentation code	https://doi.org/10.5281/zenodo.3243799	github.com/bramzandbelt/StPy

In this experiment, we used the following StPy stimulus presentation configuration files (under config/ in StPy):

• expt_3017031-05-Expt02-A.yaml
• expt_3017031-05-Expt02-B.yaml

How to use

This repository is organized as an R package. The R package structure was used to help manage dependencies, to take advantage of continuous integration for automated code testing and documentation, and to be able to follow a standard format for file organization. The package irmass depends on other R packages and non-R programs, which are listed below under Dependencies.

To download the package source as you see it on GitHub, for offline browsing, use this line at the shell prompt (assuming you have Git installed on your computer):

Install irmass package from Github:

• From R:

  devtools::install_github("bramzandbelt/irmass")
  

• From the command line:

  git clone https://github.com/bramzandbelt/irmass.git
  

Once the download is complete, open the file irmass.Rproj in RStudio to begin working with the package and compendium files. To reproduce all analyses, run the shell script analysis/bash/run_all_analyses.sh. This will run all RMarkdown notebooks in correct order. It may take several hours to complete.

Licenses

Manuscript: CC-BY-4.0 http://creativecommons.org/licenses/by/4.0/

Code: MIT http://opensource.org/licenses/MIT, year: 2019, copyright holder: Bram B. Zandbelt

Dependencies

Below is the output of sessionInfo(), showing version information about R, the OS, and attached or loaded packages:

devtools::session_info()
#> ─ Session info ──────────────────────────────────────────────────────────
#>  setting  value                       
#>  version  R version 3.6.0 (2019-04-26)
#>  os       macOS Mojave 10.14.5        
#>  system   x86_64, darwin15.6.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_US.UTF-8                 
#>  ctype    en_US.UTF-8                 
#>  tz       Europe/Amsterdam            
#>  date     2019-06-26                  
#> 
#> ─ Packages ──────────────────────────────────────────────────────────────
#>  package     * version date       lib source        
#>  assertthat    0.2.1   2019-03-21 [1] CRAN (R 3.6.0)
#>  backports     1.1.4   2019-04-10 [1] CRAN (R 3.6.0)
#>  callr         3.2.0   2019-03-15 [1] CRAN (R 3.6.0)
#>  cli           1.1.0   2019-03-19 [1] CRAN (R 3.6.0)
#>  commonmark    1.7     2018-12-01 [1] CRAN (R 3.6.0)
#>  crayon        1.3.4   2017-09-16 [1] CRAN (R 3.6.0)
#>  desc          1.2.0   2018-05-01 [1] CRAN (R 3.6.0)
#>  devtools    * 2.0.2   2019-04-08 [1] CRAN (R 3.6.0)
#>  digest        0.6.19  2019-05-20 [1] CRAN (R 3.6.0)
#>  evaluate      0.14    2019-05-28 [1] CRAN (R 3.6.0)
#>  fs            1.3.1   2019-05-06 [1] CRAN (R 3.6.0)
#>  glue          1.3.1   2019-03-12 [1] CRAN (R 3.6.0)
#>  htmltools     0.3.6   2017-04-28 [1] CRAN (R 3.6.0)
#>  knitr         1.23    2019-05-18 [1] CRAN (R 3.6.0)
#>  magrittr      1.5     2014-11-22 [1] CRAN (R 3.6.0)
#>  memoise       1.1.0   2017-04-21 [1] CRAN (R 3.6.0)
#>  packrat       0.5.0   2018-11-14 [1] CRAN (R 3.6.0)
#>  pkgbuild      1.0.3   2019-03-20 [1] CRAN (R 3.6.0)
#>  pkgload       1.0.2   2018-10-29 [1] CRAN (R 3.6.0)
#>  prettyunits   1.0.2   2015-07-13 [1] CRAN (R 3.6.0)
#>  processx      3.3.1   2019-05-08 [1] CRAN (R 3.6.0)
#>  ps            1.3.0   2018-12-21 [1] CRAN (R 3.6.0)
#>  R6            2.4.0   2019-02-14 [1] CRAN (R 3.6.0)
#>  Rcpp          1.0.1   2019-03-17 [1] CRAN (R 3.6.0)
#>  remotes       2.0.4   2019-04-10 [1] CRAN (R 3.6.0)
#>  rlang         0.3.4   2019-04-07 [1] CRAN (R 3.6.0)
#>  rmarkdown     1.13    2019-05-22 [1] CRAN (R 3.6.0)
#>  roxygen2    * 6.1.1   2018-11-07 [1] CRAN (R 3.6.0)
#>  rprojroot     1.3-2   2018-01-03 [1] CRAN (R 3.6.0)
#>  rstudioapi    0.10    2019-03-19 [1] CRAN (R 3.6.0)
#>  sessioninfo   1.1.1   2018-11-05 [1] CRAN (R 3.6.0)
#>  stringi       1.4.3   2019-03-12 [1] CRAN (R 3.6.0)
#>  stringr       1.4.0   2019-02-10 [1] CRAN (R 3.6.0)
#>  testthat      2.1.1   2019-04-23 [1] CRAN (R 3.6.0)
#>  usethis     * 1.5.0   2019-04-07 [1] CRAN (R 3.6.0)
#>  withr         2.1.2   2018-03-15 [1] CRAN (R 3.6.0)
#>  xfun          0.7     2019-05-14 [1] CRAN (R 3.6.0)
#>  xml2          1.2.0   2018-01-24 [1] CRAN (R 3.6.0)
#>  yaml          2.2.0   2018-07-25 [1] CRAN (R 3.6.0)
#> 
#> [1] /Users/bramzandbelt/surfdrive/projects/irmass/packrat/lib/x86_64-apple-darwin15.6.0/3.6.0
#> [2] /Users/bramzandbelt/surfdrive/projects/irmass/packrat/lib-ext/x86_64-apple-darwin15.6.0/3.6.0
#> [3] /Users/bramzandbelt/surfdrive/projects/irmass/packrat/lib-R/x86_64-apple-darwin15.6.0/3.6.0

Packrat takes care of dependencies in R. In addition, Stan (we used v.2.18.1) is needed.

Acknowledgment

This research project was funded through a James McDonnell Scholar Award (grant number 220020328) to Roshan Cools. We thank Roshan Cools (RC) for financial support and constructive feedback and Alexandra Sebastian (AS) for providing statistical parametric maps for the purpose of sample size estimation. We thank Ben Marwick for inspiration on how to create, organize, and describe research compendia.

Contributor roles

We specify the contribution of all people involved in the research (contributing non-authors included), according to the Contributor Role Taxonomy.

	BBZ	RvdB	RC
Conceptualization	X	-	-
Methodology	X	-	-
Software	X	-	-
Validation	X	-	-
Formal analysis	X	-	-
Investigation	-	X	-
Resources	X	-	-
Data curation	X	-	-
Writing - original draft	X	-	-
Writing - review and editing	X	X	-
Visualization	X	-	-
Supervision	X	-	-
Project administration	-	X	-
Funding acquisition	-	-	X

Contact

Bram B. Zandbelt