BANOVA: An R Package for Hierarchical Bayesian ANOVA

Abstract

In this paper, we develop generalized hierarchical Bayesian ANOVA, to assist experimental researchers in the behavioral and social sciences in the analysis of the effects of experimentally manipulated within- and between-subjects factors. The method alleviates several limitations of classical ANOVA, still commonly employed in those fields. An accompanying R Package for hierarchical Bayesian ANOVA is developed. It offers statistical routines and several easy-to-use functions for estimation of hierarchical Bayesian ANOVA models that are tailored to the analysis of experimental research. Markov Chain Monte Carlo (MCMC) simulation is used to simulate posterior samples of the parameters of each model specified by the user. The core program of all models is written in R and JAGS. After preparing the data in the required format, users simply select an appropriate model, and estimate it without any advanced coding. The main aim of the R package is to offer freely accessible resources for hierarchical Bayesian ANOVA analysis, which makes it easy to use for behavioral researchers.

Keywords: Hierarchical Bayes regression, ANOVA, Markov chain Monte Carlo, BUGS modeling