Scientific Self-Correction: The Bayesian Way

The enduring replication crisis in many scientific disciplines casts doubt on the ability of science to self-correct its findings and to produce reliable knowledge. Amongst a variety of possible methodological, social, and statistical reforms to address the crisis, we focus on replacing null hypothesis significance testing (NHST) with Bayesian inference. On the basis of a simulation study for meta-analytic aggregation of effect sizes, we study the relative advantages of this Bayesian reform, and its interaction with widespread limitations in experimental research. Moving to Bayesian statistics will not solve the replication crisis single-handely, but would eliminate important sources of effect size overestimation for the conditions we study.