Is the call to abandon p-values the red herring of the replicability crisis?

In a recent article, Cumming (2014) called for two major changes to how psychologists conduct research. The first suggested change—encouraging transparency and replication—is clearly worthwhile, but we question the wisdom of the second suggested change: abandoning p-values in favor of reporting confidence intervals (CIs) only in all psychological research reports. This article has three goals. First, we correct the false impression created by Cumming that the debate about the usefulness of NHST has been won by its critics. Second, we take issue with the implied connection between the use of NHST and the current crisis of replicability in psychology. Third, while we agree with other critics of Cumming (2014) that hypothesis testing is an important part of science (Morey et al., 2014), we express skepticism that alternative hypothesis testing frameworks, such as Bayes factors, are a solution to the replicability crisis. Poor methodological practices can compromise the validity of Bayesian and classic statistical analyses alike. When it comes to choosing between competing statistical approaches, we highlight the value of applying the same standards of evidence that psychologists demand in choosing between competing substantive hypotheses.