Despite the increasing popularity of Bayesian inference in empirical research, few practical
guidelines provide detailed recommendations for how to apply Bayesian procedures and …

Meta-analyses are essential for cumulative science, but their validity can be compromised
by publication bias. To mitigate the impact of publication bias, one may apply publication …

Tendeiro and Kiers (2019) provide a detailed and scholarly critique of Null Hypothesis
Bayesian Testing (NHBT) and its central component—the Bayes factor—that allows …

The need for a comparison between two proportions (sometimes called an A/B test) often
arises in business, psychology, and the analysis of clinical trial data. Here we discuss two …

Abstract In 1936, Sir Harold Jeffreys proposed an approximate objective Bayes factor that
quantifies the degree to which the point-null hypothesis H0 outpredicts the alternative …

Recently, several researchers have claimed that conclusions obtained from a Bayes factor
(or the posterior odds) may contradict those obtained from Bayesian posterior estimation. In …

Introduction Phenomena related to reward responsiveness have been extensively studied in
their associations with substance use and socioemotional functioning. One important task in …

Hypothesis tests are conducted not only to determine whether a null hypothesis (H0) is true
but also to determine the direction or sign of an effect. A simple estimate of the posterior …

In van Doorn et al., we outlined a series of open questions concerning Bayes factors for
mixed effects model comparison, with an emphasis on the impact of aggregation, the effect …

How accurate are people in judging someone else's knowledge based on their language
use, and do more knowledgeable people use different cues to make these judgments? We …