, Volume 38, Issue 1, pp 77-87

Demonstration and evaluation of a method for assessing mediated moderation


Mediated moderation occurs when the interaction between two variables affects a mediator, which then affects a dependent variable. In this article, we describe the mediated moderation model and evaluate it with a statistical simulation using an adaptation of product-of-coefficients methods to assess mediation. We also demonstrate the use of this method with a substantive example from the adolescent tobacco literature. In the simulation, relative bias (RB) in point estimates and standard errors did not exceed problematic levels of ±10%, although systematic variability in RB was accounted for by parameter size, sample size, and nonzero direct effects. Power to detect mediated moderation effects appears to be severely compromised under one particular combination of conditions: when the component variables that make up the interaction terms are correlated and partial mediated moderation exists. Implications for the estimation of mediated moderation effects in experimental and nonexperimental research are discussed.

This research was supported by NIMH Grant 2T32MH18387, NIDA Grant 5R01DA09757-04, and the Center for Interdisciplinary Substance Abuse Research, RTI International. We acknowledge the contributions of Matthew Fritz, Chondra Lockwood, Aaron Taylor, and Stephen G. West to this work. Portions of this research were presented at the 9th annual meeting of the Society for Prevention Research, June 2001, Washington, DC.