A systematic framework for defining R-squared measures in mediation analysis

R-squared measures of explained variance are easy to understand, naturally interpretable, and widely used by substantive researchers. In mediation analysis, however, despite recent advances in measures of mediation effect, few effect sizes have good statistical properties. Also, most of these measures are only available for the simplest three-variable mediation model, especially for R²-type measures. By decomposing the mediator into two parts (i.e., the part related to the predictor and the part unrelated to the predictor), this article proposes a systematic framework to develop new effect-size measures of explained variance in mediation analysis. The framework can be easily extended to more complex mediation models and provides more delicate R² measures for empirical researchers. A Monte Carlo simulation study is conducted to examine the statistical properties of the proposed R² effect-size measure. Results show that the new R2 measure performs well in approximating the true value of the explained variance of the mediation effect. The use of the proposed measure is illustrated with empirical examples together with program code for its implementation. (PsycInfo Database Record (c) 2025 APA, all rights reserved).