Workshop "Reproducible research practices for psychologists"

Johannes Breuer & Frederik Aust

Workshop description

For several years, psychological science has been facing a crisis of confidence fueled by concerns about low rates of successful replications of empirical findings. Different solutions have been proposed to address this issue. A key factor in these efforts is increasing transparency and computational reproducibility of psychological research. While transparent and computationally reproducible research is not necessarily more replicable, it facilitates replication attempts and helps to foster trust in empirical findings. The evolving open science ecosystem provides a variety of tools and services that can be used to implement reproducible research practices. Navigating the growing space of tools and practices, however, can be a daunting task.

Hence, the purpose of this 2 days workshop is to introduce researchers to the essential components of tailored reproducible research workflows as well as the tools for implementing them. Combining lectures with practical hands-on sessions, the workshop will focus on data analysis, reporting of results, and sharing data and materials. Regarding the tool stack, the workshop will cover version control with Git and writing reports with R Markdown as key components of a reproducible research workflow, but will also introduce other tools, such as Docker, and Binder.

Learning objectives

Upon course completion, participants should

1. be familiar with key concepts of reproducible research
2. be able to choose the appropriate tools to implement a tailored workflow
3. have gained basic proficiency of Git, R Markdown, and papaja
4. be able to manage projects and collaborate using Git and GitHub

Prerequisites

Participants should have some basic knowledge of R and some experience with RStudio.

For the hands-on parts of the workshop, you need to install R (version 4.0.0 or higher), Git, RStudio, and the R packages tinytex and papaja.

You should also set up a GitHub account or an account for the GitLab instance hosted by your institution (if that is available and you you want to use it). To set up Git and GitHub for use with RStudio, refer to Happy Git and GitHub for the useR.

Modules

| Day | Topic | Duration | Slides | Exercises | Solutions | | ---: | :---- | ------: | :----: | :-------: | :-------: | | 1 | Introduction | ~ 2 hrs | HTML, PDF | - | - | | 1 | R Markdown | ~ 2 hrs | HTML, PDF | HTML | HTML | | 1 | papaja | ~ 1.5 hrs | HTML, PDF | HTML | HTML | | 2 | Git & GitHub | ~ 1 hr | HTML, PDF | HTML | HTML | | 2 | Git & RStudio | ~ 1 hr | HTML, PDF | HTML | HTML | | 2 | Collaborate with Git & GitHub | ~ 1.5 hrs | HTML, PDF | HTML | HTML | | 2 | Other topics in reproducible research | ~ 1.5 hrs | HTML, PDF | - | - |

Citation

If you use these materials, please cite them as follows.

Aust, F., & Breuer, J. (2022). Workshop on reproducible research practices for psychologists. https://github.com/crsh/reproducible-research-practices-workshop

Acknowledgements

The workflow recommendations in this workshop are based on Klein, O., Hardwicke, T. E., Aust, F., Breuer, J., Danielsson, H., Hofelich Mohr, A., Frank, M. C. (2018). A Practical Guide for Transparency in Psychological Science. Collabra: Psychology, 4(1). doi: 10.1525/collabra.158 (Supplementary material)