Research in psychology generates complex data and often requires unique statistical analyses. These tasks are often very specific, so appropriate statistical models and methods cannot be found in accessible Bayesian tools. As a result, the use of Bayesian methods is limited to researchers and students that have the technical and statistical fundamentals that are required for probabilistic programming. Such knowledge is not part of the typical psychology curriculum and is a difficult obstacle for psychology students and researchers to overcome. The goal of the bayes4psy package is to bridge this gap and offer a collection of models and methods to be used for analysing data that arises from psychological experiments and as a teaching tool for Bayesian statistics in psychology. The package contains the Bayesian t-test and bootstrapping along with models for analysing reaction times, success rates, and tasks utilizing colors as a response. It also provides the diagnostic, analytic and visualization tools for the modern Bayesian data analysis workflow.
- Demšar, J., Repovš, G., & Štrumbelj, E. (2020). bayes4psy—An Open Source R Package for Bayesian Statistics in Psychology. Frontiers in psychology, 11, 947.
- Full paper: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.00947/full
- CRAN repository: https://cran.r-project.org/web/packages/bayes4psy/index.html
- GitHub: https://github.com/bstatcomp/bayes4psy