Publications [#352516] of Eric Laber
Papers Published
- Zhang, B; Tsiatis, AA; Laber, EB; Davidian, M. "Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions.." Biometrika 100.3 (2013). [doi]
(last updated on 2026/01/13)Abstract:
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.