Tests of statistical interactions (or tests of moderation effects) in personality disorder research are a common way for researchers to examine nuanced hypotheses relevant to personality pathology. However, the nature of statistical interactions makes them difficult to reliably detect in many research scenarios. The present study used a flexible, simulation-based approach to estimate statistical power to detect trait-by-trait interactions common to psychopathy research using the Triarchic model of Psychopathy and the Psychopathic Personality Inventory. Our results show that even above-average sample sizes in these literatures (e.g., N = 428) provide inadequate power to reliably detect trait-by-trait interactions, and the sample sizes needed to detect interaction effect sizes in realistic scenarios are extremely large, ranging from 1,300 to 5,200. The implications for trait-by-trait interactions in psychopathy are discussed, as well as how the present findings might generalize to other areas of personality disorder research. We provide recommendations for how to design research studies that can provide informative tests of interactions in personality disorder research, but also highlight that a more realistic option is to abandon the traditional approach when testing for interaction effects and adopt alternative approaches that may be more productive.

Statistical interactions, whether tested using multiple regression or related statistical models (e.g., analysis of variance), occur when one variable’s effect on an outcome is dependent on values of a separate variable, referred to as a moderator variable. Personality disorder research often includes tests for statistical interactions. These tests typically take the form of an interaction between maladaptive traits and a moderator variable, including experimental condition (Chapman et al., 2010), demographic variables such as race (Haliczer et al., 2020) or sex (Verona et al., 2012), developmental variables (Gratz et al., 2011), or other traits (Lilienfeld et al., 2019; Vize et al., 2016). Such tests allow researchers...