JSM 2005 - Toronto

Abstract #302755

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 251
Type: Invited
Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor: General Methodology
Abstract - #302755
Title: Sensitivity Analysis Comparing Outcomes Measured Only in a Subset Selected Post-randomization, with Application to HIV Vaccine Trials
Author(s): Peter Gilbert*+ and Bryan Shepherd and Yannis Jemiai and Andrea Rotnitzky
Companies: Fred Hutchinson Cancer Research Center and University of Washington and Harvard School of Public Health and Harvard School of Public Health
Address: Statistical Center for HIV/AIDS Research and Prevention, Seattle, WA, 98109,
Keywords: causal inference ; HIV studies ; principal stratification ; Maximum likelihood ; viral load
Abstract:

Consider a randomized trial in which a study endpoint is measured only in a subset of study participants selected after randomization. For example, in placebo-controlled preventive HIV vaccine efficacy trials, HIV viral load is only measured in participants who acquire HIV infection during followup. This talk presents a method of sensitivity analysis for inferences on the average causal effect (ACE) of randomization to vaccine on viral load at a given covariate level in the always-infected principal stratum (i.e., those who would be infected whether they were assigned vaccine or placebo). We assume stable unit treatment values (SUTVA), randomization, and that subjects assigned vaccine who become HIV infected also would have been infected had they been assigned placebo (monotonicity). It is unknown which of those infected subjects assigned placebo are in the always-infected principal stratum, but the probability of this event can be modeled conditional on covariates, the observed viral load, and a specified sensitivity parameter.

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Revised March 2005