Abstract
Multiple statistical testing (or multiple comparisons) occurs quite often in psychiatric research since it remains common for a given sample to have multiple exposures and outcomes assessed concurrently 1. One reason for this is that clinical presentations in psychiatry are complex phenomena whose etiologies appear to comprise multiple environmental and biological factors with small‐to‐moderate magnitudes 2. So, although complex etiologies could be modeled using interactions and advanced multivariable statistical models, it is common that they need crude estimates of novel variables, increasing the probability of dealing with multiple comparisons.