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Optimal Dynamic Treatment Regimes
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2003 · Vol. 65(2) · pp. 331–355
Susan A. Murphy✉(University of Michigan–Ann Arbor)
Abstract
Summary A dynamic treatment regime is a list of decision rules, one per time interval, for how the level of treatment will be tailored through time to an individual’s changing status. The goal of this paper is to use experimental or observational data to estimate decision regimes that result in a maximal mean response. To explicate our objective and to state the assumptions, we use the potential outcomes model. The method proposed makes smooth parametric assumptions only on quantities that are directly relevant to the goal of estimating the optimal rules. We illustrate the methodology proposed via a small simulation.
Advanced Causal Inference TechniquesStatistical Methods and InferenceStatistical Methods in Clinical TrialsParametric statisticsInterval (graph theory)Observational studyComputer scienceMathematical optimizationState (computer science)EconometricsMathematicsStatisticsAlgorithm
Funding
- National Science Foundation
- National Institute on Drug Abuse
Citations
1,031
FWCI
15.64
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44
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References
Bayesian Inference for Causal Effects: The Role of Randomization
The Annals of Statistics · 1978 · 2,510 citations
Evaluating Influence Diagrams
Operations Research · 1986 · 1,266 citations
Dynamic Programming
Science · 1966 · 13,052 citations
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