Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”

In order to test their hypotheses, psychologists increasingly favor the Bayes factor , the standard Bayesian measure of relative evidence between two competing statistical models. The Bayes factor has an intuitive interpretation and allows a comparison between any two models, even models that are complex and nonnested. In this introduction to the special issue “Bayes factors for Testing Hypotheses in Psychological Research: Practical Relevance and New Developments”, we first highlight the basic properties of the Bayes factor, stressing its advantages over classical significance testing. Next, we briefly discuss statistical software packages that are useful for researchers who wish to make the transition from p values to Bayes factors. We end by providing an overview of the contributions to this special issue. The contributions fall in three partly overlapping categories: those that present new philosophical insights, those that provide methodological innovations, and those that demonstrate practical applications