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

Bayesian analysis of factorial designs.

Author information

1
Department of Psychological Sciences, University of Missouri.
2
School of Psychology, Cardiff University.
3
Department of Psychological Methods, University of Amsterdam.

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.

PMID:
27280448
DOI:
10.1037/met0000057
[Indexed for MEDLINE]

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