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Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.

Publication ,  Journal Article
Zhang, B; Tsiatis, AA; Laber, EB; Davidian, M
Published in: Biometrika
2013

A dynamic treatment regime is a list of sequential decision rules for assigning treatment based on a patient's history. Q- and A-learning are two main approaches for estimating the optimal regime, i.e., that yielding the most beneficial outcome in the patient population, using data from a clinical trial or observational study. Q-learning requires postulated regression models for the outcome, while A-learning involves models for that part of the outcome regression representing treatment contrasts and for treatment assignment. We propose an alternative to Q- and A-learning that maximizes a doubly robust augmented inverse probability weighted estimator for population mean outcome over a restricted class of regimes. Simulations demonstrate the method's performance and robustness to model misspecification, which is a key concern.

Duke Scholars

Published In

Biometrika

DOI

ISSN

0006-3444

Publication Date

2013

Volume

100

Issue

3

Location

England

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1403 Econometrics
  • 0104 Statistics
  • 0103 Numerical and Computational Mathematics
 

Citation

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Chicago
ICMJE
MLA
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Zhang, B., Tsiatis, A. A., Laber, E. B., & Davidian, M. (2013). Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions. Biometrika, 100(3). https://doi.org/10.1093/biomet/ast014
Zhang, Baqun, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. “Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.Biometrika 100, no. 3 (2013). https://doi.org/10.1093/biomet/ast014.
Zhang B, Tsiatis AA, Laber EB, Davidian M. Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions. Biometrika. 2013;100(3).
Zhang, Baqun, et al. “Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.Biometrika, vol. 100, no. 3, 2013. Pubmed, doi:10.1093/biomet/ast014.
Zhang B, Tsiatis AA, Laber EB, Davidian M. Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions. Biometrika. 2013;100(3).
Journal cover image

Published In

Biometrika

DOI

ISSN

0006-3444

Publication Date

2013

Volume

100

Issue

3

Location

England

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1403 Econometrics
  • 0104 Statistics
  • 0103 Numerical and Computational Mathematics