Common Error 7: Converting a Continuous Variable into Categorical Without Appropriate Justification Researchers sometimes dichotomize continuous moderators to facilitate analysis (Aguinis, 2017; Becker et al., 2023; Rasoolimanesh et al., 2021). Our review found 10.95% of studies used methods ...
Evaluation and analysis issues Common Error 6: Low Statistical Power Moderation tests are known to have lower statistical power than main effect analyses due to various factors (Aguinis et al., 2017; Carte Russell, 2003; Dawson, 2014; Memon et al., 2019). While neglect of this issue ...
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 ...
18. 投稿时，被要求做Measurement invariance，什么是Measurement invariance？ 答： Measurement invariance is also referred to as measurement equivalence. 测量不变性又称为测量恒等性。 我们通常使用测量恒等性来确认群组间的差异是来自于不同群组潜在变数的内含或意义， 换句话说，无法确立测量恒等性 ...
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