Analysis of variance (ANOVA) is the standard procedure for statistical inference in factorial designs. Typically, ANOVAs are executed using frequentist statistics, where p-values determine statistical significance in an all-or-none fashion. In recent years, the Bayesian approach to statistics is increasingly viewed as a legitimate alternative to the p-value. However, the broad adoption of Bayesian statistics-and Bayesian ANOVA in particular-is frustrated by the fact that Bayesian concepts are rarely taught in applied statistics courses. Consequently, practitioners may be unsure how to conduct a Bayesian ANOVA and interpret the results. Here we provide a guide for executing and interpreting a Bayesian ANOVA with JASP, an open-source statistical software program with a graphical user interface. We explain the key concepts of the Bayesian ANOVA using two empirical examples.

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Keywords Analysis of Variance, Bayes Factor, Hypothesis Test, JASP, Posterior distribution, Tutorial
Persistent URL dx.doi.org/10.3917/anpsy1.201.0073
Journal Annee Psychologique
Citation
van den Bergh, D, van Doorn, J, Marsman, M, Draws, T, Kesteren, E.-J, Derks, K, … Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a bayesian ANOVA in JASP Tutoriel pour réaliser et interpréter une analyse de variance bayésienne dans JASP. Annee Psychologique, 120(1), 73–96. doi:10.3917/anpsy1.201.0073