Abstract #302356

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JSM 2003 Abstract #302356
Activity Number: 155
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #302356
Title: Issues in Causal Inference from High-Dimensional Longitudinal Data
Author(s): James M. Robins*+
Companies: Harvard School of Public Health
Address: 361 Harvard Street, Cambridge, MA, 02138-4235,
Keywords:
Abstract:

I discuss new ideas and open problems in statistical methods for drawing causal inferences and for estimating optimal treatment strategies from either high-dimensional observational or randomized trial data. Some thoughts on Bayes-frequentist compromises are considered. The goal is to combine the robustness of non-likelihood-based, so-called doubly robust procedures that use models for the treatment process (thus violating the likelihood and conditionality principles) with the synthetic ability of Bayes procedures to use the data to update prior uncertainty with a posterior.

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Revised March 2003