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Activity Number: 214
Type: Invited
Date/Time: Monday, August 5, 2013 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #307276
Title: Estimating the Average Treatment Effect on Mean Survival Time When Treatment Is Time-Dependent and Censoring Is Dependent
Author(s): Douglas Earl Schaubel*+ and Qi Gong
Companies: University of Michigan and Amgen
Keywords: causal inference ; dependent censoring ; survival analysis ; treatment effect

We propose methods for estimating the average difference in restricted mean survival time attributable to a time-dependent treatment. In the data structure of interest, the time until treatment is received and the pre-treatment death hazard are both heavily influenced by a longitudinal process. In addition, subjects may experience periods of treatment ineligibility. The pre-treatment death hazard is modeled using inverse weighted partly conditional methods, while the post-treatment hazard is handled through Cox regression. Subject-specific differences in pre- versus post-treatment survival are estimated, then averaged in order to estimate the average treatment effect among the treated. Asymptotic properties of the proposed estimators are derived and evaluated in finite samples through simulation. The proposed methods are applied to liver failure data obtained from a national organ transplant registry.

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

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