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Activity Number: 539
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #316926
Title: Causal Mediation Analysis with Measurement Error in Both Exposure and Mediator
Author(s): Cheng Zheng*
Companies: University of Wisconsin - Milwaukee
Keywords: Causal inference ; Mediation analysis ; Measurement error
Abstract:

Causal mediation analysis is important to understand how an exposure affects certain disease outcome. When the exposure and mediator are self-reported variables, they are subject to measurement error and will cause bias in the estimator of both direct, indirect and mediator effects. In this work, we proposed a regression calibration method to correct the inaccurate self-reported data with objective measured biomarker subsample. We perform simulation studies to showed the bias using traditional regression approach ignoring measurement error and we showed that our proposed method works well under rare disease assumption. We applied our method to the Women's Health Initiative data to assess the relationship between energy intake, physical activity, BMI and various chronic diseases.


Authors who are presenting talks have a * after their name.

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