Learning about hypothesis evaluation using the Bayes factor could enhance psychological
research. In contrast to null-hypothesis significance testing it renders the evidence in favor of …

How to correctly interpret interaction effects has been largely discussed in scientific
literature. Nevertheless, misinterpretations are still frequently observed, and neuroscience is …

Bayesian parameter estimation and Bayesian hypothesis testing present attractive
alternatives to classical inference using confidence intervals and p values. In part I of this …

Unplanned optional stop** rules have been criticized for inflating Type I error rates under
the null hypothesis significance testing (NHST) paradigm. Despite these criticisms, this …

We illustrate the Bayesian approach to data analysis using the newly developed statistical
software program JASP. With JASP, researchers are able to take advantage of the benefits …

Bayes factors provide a symmetrical measure of evidence for one model versus another (eg
H1 versus H0) in order to relate theory to data. These properties help solve some (but not …

In management research, empirical data are often analyzed using p-value null hypothesis
significance testing (pNHST). Here we outline the conceptual and practical advantages of an …

Researchers often have difficulties collecting enough data to test their hypotheses, either
because target groups are small or hard to access, or because data collection entails …

As the field of psychology struggles to trust published findings, replication research has
begun to become more of a priority to both scientists and journals. With this increasing …

This study explored the roles of exposure frequency, aural enhancement (AE) of input, and
individual differences in working memory (WM) during L2 incidental vocabulary learning …