“…Unlike p-values, Bayes factors are consistent under both the null and the alternative hypothesis, meaning that as data accumulate indefinitely the chance that the Bayes factor points to the correct hypothesis approaches 1. This property enables hypothesis testers to stop whenever the evidence is deemed to be sufficiently compelling, and this allows for a flexible testing regime that is both efficient and ethical (Berger and Wolpert, 1988;Edwards et al, 1963;Rouder, 2014;Schönbrodt et al, 2017;Stefan, Schönbrodt, et al, 2020;Wagenmakers et al, 2022; for a discussion see de Heide and Grünwald, 2021;Hendriksen et al, 2021;Sanborn and Hills, 2014). 1 Third, the Bayesian framework allows researchers to quantify evidence in favor of the null hypothesis as well as the alternative hypothesis (Gallistel, 2009;Rouder et al, 2009).…”