bayes4psy-An Open Source R Package for Bayesian Statistics in Psychology

Area of Science:

• Psychology
• Statistics
• Computational Statistics

Background:

• Psychological research generates complex data requiring specialized statistical analyses.
• Accessible Bayesian tools often lack the specific models needed for psychological data.
• A gap exists between the need for Bayesian methods in psychology and researchers' technical expertise.

Purpose of the Study:

• To bridge the gap in Bayesian statistical analysis for psychology.
• To provide a collection of models and methods for analyzing psychological data.
• To serve as an educational tool for teaching Bayesian statistics in psychology.

Main Methods:

• Development of the bayes4psy R package.
• Inclusion of Bayesian t-test and bootstrapping methods.
• Implementation of models for reaction times, success rates, and color-response tasks.
• Integration of diagnostic, analytic, and visualization tools for Bayesian workflows.

Main Results:

• The bayes4psy package offers specialized Bayesian models for psychological data analysis.
• It includes essential tools like Bayesian t-tests and bootstrapping.
• Provides methods for analyzing reaction times, success rates, and color-based tasks.
• Offers comprehensive tools for the modern Bayesian data analysis workflow.

Conclusions:

• bayes4psy democratizes Bayesian statistics for psychology researchers and students.
• The package facilitates the analysis of complex psychological data.
• It serves as a valuable teaching resource for Bayesian methods in psychology.