Psychological Methods · 2006 · 1.7K citations · 55 references
Public HealthBiostatisticsPsychologyCausal InferenceExperimental DesignMediationCausal Effect EstimationMediation AnalysisModerator AnalysisMultilevel Meta-analysisMultilevel ModelingStructural Equation ModelingIndirect EffectsModerated MediationMultilevel ContextMultilevel Mediation AnalysisMultilevel Moderator ModelsNormal ApproximationRandom Effects DistributionTotal Effect
The authors introduce procedures to estimate direct, indirect, and total effects in multilevel models where all variables and effects are at Level 1 and random. They derive formulas for the means, variances, and sampling variances of indirect and total effects, and extend the methods to test moderated mediation in multilevel contexts. Simulations confirm that the estimators are largely unbiased, with normal‑based confidence intervals performing well under normal random effects but less so when nonnormal, and an applied example illustrates the methods’ practicality.
The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects. Simulations show that the estimates are unbiased under most conditions. Confidence intervals based on a normal approximation or a simulated sampling distribution perform well when the random effects are normally distributed but less so when they are nonnormally distributed. These methods are further developed to address hypotheses of moderated mediation in the multilevel context. An example demonstrates the feasibility and usefulness of the proposed methods.
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Multiple regression: testing and interpreting interactions
Choice Reviews Online · 1992 · 37.2K citations