Publication | Open Access
A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP
112
Citations
41
References
2019
Year
Unknown Venue
Bayesian StatisticBayesian StatisticsQuantitative MethodsBayesian Decision TheoryData ScienceStatistical ComputingBayesian AnovaEducationBayesian ConceptsBiostatisticsStatistical InferenceBayesian MethodsPublic HealthStatisticsBayesian InferenceBayesian Hierarchical ModelingApproximate Bayesian Computation
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. Herewe 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 twoempirical examples.
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