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Common Error 10: Debate on Mean-Center/Standardize X and M
Mean-centering in moderation analysis is debated. Its principal value is enhancing coefficient interpretability, not solving multicollinearity (Aguinis et al., 2017; Becker et al., 2023; Dawson, 2014). For continuous variables, centering allows main effects (e.g., b1 for X) to represent the effect when the moderator (M) is at its mean, aiding interpretation (Aiken et al., 1991; Aguinis et al., 2017). For binary moderators, centering is discouraged as it obscures the reference group's meaning (Becker et al., 2023). Thus, we recommend mean-centering continuous predictors but using uncentered binary variables. Regardless of centering, diagnosing multicollinearity via VIFs is essential (Hair et al., 2009). If severe collinearity persists, consider residual centering (orthogonalization).
调节分析:常见问题十 关于变量是否中心化的争议与误用
是否对构建交互项的自变量(X)和调节变量(M)进行均值中心化,是一个长期的方法学讨论点。我们的综述发现,42.70%的研究明确报告进行了此类处理。核心共识是:中心化主要目的是提升系数解释性,而非根本解决多重共线性。中心化后,X的主效应系数代表当M处于均值水平时X对Y的影响,这通常比解释“当X和M均为0时”更具现实意义。
问题实质:
中心化好比把坐标原点移到数据分布的中心,让主要参数的解读(简单斜率)变得更直观、更有意义,但并没有改变变量间的内在关系。
解决建议
连续变量建议中心化:对于连续的自变量和调节变量,建议进行均值中心化,以方便对简单斜率的解释(Aiken等, 1991)。
二分变量不建议中心化:对于二分类调节变量(如性别:0/1),应使用原始编码,因为中心化会使其参考点失去清晰的实质含义(Becker等, 2023)。
始终诊断共线性:无论是否中心化,都必须计算并报告所有预测变量的方差膨胀因子(VIF)。若VIF过高(如>10),表明存在严重的多重共线性问题,需考虑其他方法(如正交化)或模型设定。
Reference
Aguinis, H., Edwards, J. R., & Bradley, K. J. (2017). Improving our understanding of moderation and mediation in strategic management research. Organizational Research Methods, 20(4), 665-685.
Becker, J. M., Cheah, J. H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM's most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321-346.
Dawson, J. F. (2014). Moderation in management research: What, why, when, and how. Journal of Business and Psychology, 29(1), 1-19.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). SAGE Publications.
Memon, M. A., Cheah, J. H., Ramayah, T., Ting, H., Chuah, F., & Cham, T. H. (2019). Moderation analysis: Issues and guidelines. Journal of Applied Structural Equation Modeling, 3(1), i-xi.
Xu, Y., & Shiau, W. L. (2026). Moderation analysis in business and management research: Common issues, solutions, and guidelines for future research. International Journal of Information Management, 86, 102995.
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