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

Ÿ  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）。

Ÿ  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）。

Ÿ  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.