Common Error 5: Nonlinear Monotonic Transformations on X, M, and Y Without Rational Justification To meet parametric assumptions (e.g., normality), researchers sometimes apply transformations (e.g., log, square root) to variables X, M, or Y. In our review, 13.50% of studies did so. Arbitrary ...
Measurement, sampling, and scaling issues Common Error 4: Lack of Attention to Measurement Errors of the Interaction Term Measurement error is a primary source of low statistical power in moderation analysis, biasing estimates and attenuating effects (Aguinis, 2017; Carte Russell, 20 ...
Common Error 3: Failure to Predefine Hypotheses and Their Functional Forms Moderation analyses using NHST require a priori hypothesis specification, as they test predetermined expectations (Becker et al., 2023; Dawson, 2014; Rasoolimanesh et al., 2021). Our review found that 34.67% of studies ...
Common Error 2: Insufficient Theoretical Justification for Moderation Hypotheses Many studies lack sufficient theoretical justification for their moderation hypotheses, a persistent issue documented by several scholars (Carte Russell, 2003; Dawson, 2014; Landis Dunlap, 2000; Rasoolima ...
Common Error 1: Using Moderation Analysis Driven by Problematic Motives A prevalent issue is the use of moderation analysis without adequate theoretical justification (Dawson, 2014; Memon et al., 2019; Becker et al., 2023). A crucial first step is determining if a moderation model is theoretica ...
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