This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 212
Type: Invited
Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract - #305986
Title: Estimating Optimal Dynamic Treatment Regimes with Shared Decision Rules Across Stages: An Extension of Q-learning
Author(s): Bibhas Chakraborty*+ and Erica E.M. Moodie
Companies: Columbia University and McGill University
Address: , , ,
Keywords: dynamic treatment regime ; non-regularity ; soft-threshold ; shared ; bootstrap
Abstract:

Dynamic treatment regimes (DTR) offer a framework to operationalize the adaptive multistage decision making in clinical practice. Formally, a DTR is a set of decision rules, one per stage; each decision rule takes a patient's treatment and covariate history as input, and outputs a recommended treatment. In some studies, these decision rules are shared across stages of treatment, i.e. the decision rule at each stage is the same function of the history available at that stage. Because of this sharing phenomenon, recursive methods like Q-learning that move backward through stages are not suitable; simultaneous estimation techniques are necessary. In this paper, we propose a simultaneous estimation procedure for the optimal DTR with shared decision rules, adjusting for non-regularity via thresholding. We compare the performance of the proposed method to other approaches through simulation.


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