Abstract 411: New estimators for mediation effects in complex sampling schemes: A comparison with applications

Abstract

Abstract Mediation analysis examines the indirect effects via a third variable on the pathway between exposures and outcomes. For the finite-population surveys, that often use stratified cluster sampling, the conventional methods assuming simple random sampling are not appropriate. The point estimation of the effect can be corrected using sampling weights, but the standard error needs further improvement. Recent studies have integrated mediation analysis with balanced repeated replication for standard error estimation. Alternative estimators include Jackknife repeated replication (JRR), bootstrap, and Taylor series linear approximation (TSE). This study proposes new standard error estimators by incorporating the classic linear mediation analysis with JRR, bootstrap, and TSE for complex surveys and compares them using Monte Carlo simulations. The preliminary results show that replication methods have lower Type-I error rates and higher confidence-interval coverage rates than conventional methods. The proposed methods are applied to National Health Interview Surveys to explore the mediation effects on the pathway between cancer survivors' health status and employment status. Citation Format: Yujiao Mai, Deo Kumar Srivastava. New estimators for mediation effects in complex sampling schemes: A comparison with applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 411.