Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural equation modeling (SEM) in estimating mediation models with multiple mediators and multiple outcomes. We also describe the estimation and interpretation of a 2→1→1 multilevel mediation model in which the first, second, and third numbers correspond to the measurement levels of the independent, mediator, and outcome variables, respectively. We present two numerical examples that use simulated data based on published studies in adolescence research to demonstrate how to specify, estimate, and interpret the results of single-level and multilevel mediation analyses to answer key research questions. We briefly discuss underlying assumptions required to make a valid causal interpretation of a mediation analysis.
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