Online Program Home
My Program

Abstract Details

Activity Number: 3
Type: Invited
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract #318479
Title: Survival Mediation Analysis Using Semiparametric Probit Models with Application to Integrative Genomics
Author(s): Yen-Tsung Huang* and Tianxi Cai
Companies: Brown University and Harvard
Keywords: Mediation analysis ; Integrative genomics ; Survival analysis ; Nonparametric maximum likelihood estimator ; Semiparametric probit models ; Causal inference

Causal mediation modeling has become a popular approach for studying the effect of an exposure on an outcome through mediators. Currently literature on mediation analyses with survival outcomes largely focused on settings with a single mediator and quantified the mediation effects on the hazard, log hazard and log survival time (Lange and Hansen 2011; VanderWeele 2011). In this paper, we propose a multi-mediator model for survival data by employing a flexible semiparametric probit model. We characterize path-specific effects (PSEs) of the exposure on the outcome mediated through specific mediators. We derive closed form expressions for PSEs on a transformed survival time and the survival probabilities. Statistical inference on the PSEs is developed using a nonparametric maximum likelihood estimator under the semiparametric probit model and the functional Delta method. Results from simulation studies suggest that our proposed methods perform well in finite sample. We illustrate the utility of our method in a genomic study of glioblastoma multiforme survival.

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

Back to the full JSM 2016 program

Copyright © American Statistical Association