Department of Psychiatry.
Department of Psychology and Neuroscience.
Personal Disord. 2023 Jan;14(1):118-126. doi: 10.1037/per0000582. Epub 2022 Jun 23.
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., = 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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
测试统计交互作用（或调节效应测试）在人格障碍研究中是研究人员检验与人格病理学相关的细微假设的常用方法。然而，统计交互作用的性质使得它们在许多研究情况下难以可靠地检测到。本研究使用灵活的基于模拟的方法，使用三因素模型和精神病态人格量表，估计了检测常见于精神病态研究的特质-特质相互作用的统计功效。我们的结果表明，即使在这些文献中使用平均样本量（例如，n = 428）也不足以可靠地检测特质-特质相互作用，并且在现实情况下检测交互效应大小所需的样本量非常大，范围从 1300 到 5200。讨论了精神病态中特质-特质相互作用的意义，以及本研究结果如何推广到其他人格障碍研究领域。我们提供了如何设计研究的建议，这些研究可以为人格障碍研究中的交互作用提供有意义的测试，但也强调了当测试交互效应时放弃传统方法并采用可能更有成效的替代方法是更现实的选择。（PsycInfo 数据库记录（c）2023 APA，保留所有权利）。
