Adjustments for making multiple comparisons in large bodies of data are recommended to
avoid rejecting the null hypothesis too readily. Unfortunately, reducing the type I error for null
associations increases the type II error for those associations that are not null. The
theoretical basis for advocating a routine adjustment for multiple comparisons is the
“universal null hypothesis” that “chance” serves as the first-order explanation for observed
phenomena. This hypothesis undermines the basic premises of empirical research, which …