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Activity Number: 88 - SPEED: Causal Inference and Related Methodology Part 2
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 5:05 PM to 5:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #307501
Title: Mediation Analysis with a Censored Mediator in a Case–control Study
Author(s): Jian Wang* and Jing Ning and Sanjay Shete
Companies: UT MD Anderson Cancer Center and The University of Texas MD Anderson Cancer Center and UT MD Anderson Cancer Center
Keywords: Mediation analysis; censored mediator; case–control study; indirect effects; semiparametric accelerated failure time model

Mediation analysis is an approach for assessing the direct and indirect effects of an initial variable on an outcome through a mediator. Mediation analysis can involve a censored mediator. The current research for mediation analysis with a censored mediator focuses on scenarios of continuous outcomes. However, case-control study is one of the most commonly used design in genetic epidemiologic studies in which the outcome is binary. Another challenge when utilizing retrospective case-control data for mediation analysis is that it may lead to biased estimation when assessing correlation between initial variable and mediator. In this study, we propose an approach to analyze the mediation model with a censored mediator for a case–control study design, based on the semiparametric accelerated failure time model along with a pseudo-likelihood function. We adapted the measures for assessing the indirect and direct effects using counterfactual definitions. We conducted simulations to investigate the performance of the proposed approach and applied it to the mediation study of genetic variants, a woman’s age at menopause and type-2 diabetes based on a case–control study of type-2 diabetes.

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

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