Refinements to Effect Sizes for Tests of Categorical Moderation and Differential Prediction
改进了Nye和Sackett提出的分类调节分析标准化效应量d Mod，通过考虑预测变量分布不对称性、分别量化正负差异，并支持非参数效应量计算，提供了R语言软件实现。
We provide a follow-up treatment of Nye and Sackett’s (2017) recently proposed d Mod standardized effect-size measures for categorical-moderation analyses. We offer several refinements to Nye and Sackett’s effect-size equations that increase the precision of d Mod estimates by accounting for asymmetries in predictor distributions, facilitate the interpretation of moderated effects by separately quantifying positive and negative differences in prediction, and permit the computation of nonparametric effect sizes. To aid in the implementation of our refinements to d Mod , we provide software written in the R programming language that computes Nye and Sackett’s effect sizes with all of our refinements and that includes options for easily computing bootstrapped standard errors and bootstrapped confidence intervals.