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Activity Number: 674
Type: Invited
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #318213
Title: Doubly Robust Estimation of Optimal Treatment Regime in Additive Hazards Regression
Author(s): Wenbin Lu* and Suhyun Kang
Companies: North Carolina State University and North Carolina State University
Keywords: A-learning ; additive hazards regression ; doubly robust estimation ; individualized treatment regime ; personalized medicine

Learning optimal individualized treatment regime has recently attracted a lot of attention for personalized medicine. In this talk, I will present a doubly robust estimation method for estimating optimal individualized treatment regime in additive hazards regression with censored survival data. By properly adjusting for time-dependent propensity scores, the new method is robust against the misspecification of the main effects of covariates, and therefore enjoys the doubly robust property as in the A-learning estimation for uncensored data. Simulations and a real data application will be shown to illustrate the performance of the proposed method.

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

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