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Bayesian (non)linear random effects mediation models: Evaluating the impact of omitting confounders

Ziwei Zhang1, Nidhi Kohli1, Eric F Lock2

  • 1Department of Educational Psychology, University of Minnesota.

Psychological Methods
|September 25, 2025
PubMed
Summary

Researchers developed Bayesian nonlinear random effects mediation models (B(N)REMM) to directly estimate linear and nonlinear longitudinal mediation. Omitting confounders negatively impacts parameter recovery in these models, especially for segmented trends.

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