Bayesian analysis of factorial designs.
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
Department of Psychological Sciences, University of Missouri.
Jeffrey N
JN
Rouder
School of Psychology, Cardiff University.
Richard D
0000-0001-9220-3179
RD
Morey
Department of Psychological Methods, University of Amsterdam.
Josine
J
Verhagen
Department of Psychological Sciences, University of Missouri.
April R
AR
Swagman
Department of Psychological Methods, University of Amsterdam.
Eric-Jan
EJ
Wagenmakers
D000704:Analysis of Variance; D001499:Bayes Theorem; D006801:Humans; D015233:Models, Statistical; D012107:Research Design