#3208. How to Choose between Different Bayesian Posterior Indices for Hypothesis Testing in Practice

October 2026publication date
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Journal’s subject area:
Statistics and Probability;
Arts and Humanities (miscellaneous);
Experimental and Cognitive Psychology;
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Abstract:
Hypothesis testing is an essential statistical method in experimental psychology and the cognitive sciences. Bayesian hypothesis testing is concerned with various posterior indices for significance and the size of an effect. In this research, various Bayesian posterior indices which have been proposed in the literature are compared and their benefits and limitations are discussed. The comparison shows that conceptually not all proposed Bayesian alternatives to NHST and p-values are beneficial, and the usefulness of some indices strongly depends on the study design and research goal. The comparison reveals that there exist at least two candidates among the available Bayesian posterior indices which have appealing theoretical properties and are widely underused in the cognitive sciences.
Keywords:
Bayes factor; Bayesian hypothesis testing; Bayesian posterior indices; e-value; equivalence testing; MAP-based p-value; probability of direction (PD); ROPE

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