During multiple testing, researchers often adjust their alpha level to control the familywise error rate for a statistical inference about a joint union alternative hypothesis (e.g., “ H1 or H2 ”). However, in some cases, they do not make this inference.

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p -hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view.