Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions

TLDR

This article provides a guide for researchers to properly construct and conduct analyses of conditional indirect effects, also known as moderated mediation effects. The article aims to guide researchers in properly defining, estimating, and testing moderated mediation effects, clarifying conflicting definitions and outlining hypothesis‑testing approaches. The authors present methods for defining, estimating, and testing moderated mediation, including standard‑error calculations, bootstrapping recommendations, probing techniques such as simple slopes and Johnson‑Neyman, and an SPSS macro to implement these procedures. An example from the Michigan Study of Adolescent Life Transitions demonstrates that the indirect effect of intrinsic student interest on mathematics performance via teacher perceptions of talent is moderated by student math self‑concept.

Abstract

This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated mediation and describe approaches for estimating and testing a variety of hypotheses involving conditional indirect effects. We introduce standard errors for hypothesis testing and construction of confidence intervals in large samples but advocate that researchers use bootstrapping whenever possible. We also describe methods for probing significant conditional indirect effects by employing direct extensions of the simple slopes method and Johnson-Neyman technique for probing significant interactions. Finally, we provide an SPSS macro to facilitate the implementation of the recommended asymptotic and bootstrapping methods. We illustrate the application of these methods with an example drawn from the Michigan Study of Adolescent Life Transitions, showing that the indirect effect of intrinsic student interest on mathematics performance through teacher perceptions of talent is moderated by student math self-concept.