56: Longitudinal mediation analysis with multiple mediators: an unbiased estimator for cumulative effect

Music City Center 

Mediation analysis examines the pathways between predictors and outcomes through intermediate variables. We extend conventional mediation analysis by incorporating cumulative impact of predictors on outcomes over time in longitudinal processes. We derive the cumulative direct and indirect effects of predictors on outcomes from multiple time points, allowing for multiple independent mediators at each time point. Specifically, our proposed model accounts for the effects of predictors and outcomes from all previous time points as mediators for the outcome variable at a given time point. We evaluate cumulative indirect effects and their standard errors using three approaches: exact form, the delta method, and the bootstrap procedure. We demonstrate that the indirect effect estimators from least-squared method are unbiased under certain conditions, with the unbiasedness illustrated in simulation studies. We show that three types of standard error estimates are numerically similar, with the bootstrap method recommended due to the complexity of the closed forms of the other two methods.

longitudinal mediation analysis

multiple mediators 

ENAR