Bayesian analysis of factorial designs

Psychol Methods. 2017 Jun;22(2):304-321. doi: 10.1037/met0000057. Epub 2016 Jun 9.

Abstract

This article provides a Bayes factor approach to multiway analysis of variance (ANOVA) that allows researchers to state graded evidence for effects or invariances as determined by the data. ANOVA is conceptualized as a hierarchical model where levels are clustered within factors. The development is comprehensive in that it includes Bayes factors for fixed and random effects and for within-subjects, between-subjects, and mixed designs. Different model construction and comparison strategies are discussed, and an example is provided. We show how Bayes factors may be computed with BayesFactor package in R and with the JASP statistical package. (PsycINFO Database Record

MeSH terms

  • Analysis of Variance*
  • Bayes Theorem*
  • Humans
  • Models, Statistical*
  • Research Design*