Publications [#352344] of Eric Laber
Papers Published
- Schulte, PJ; Tsiatis, AA; Laber, EB; Davidian, M. "Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes.." Stat Sci 29.4 (November, 2014): 640-661. [doi]
(last updated on 2026/01/14)Abstract:
In clinical practice, physicians make a series of treatment decisions over the course of a patient's disease based on his/her baseline and evolving characteristics. A dynamic treatment regime is a set of sequential decision rules that operationalizes this process. Each rule corresponds to a decision point and dictates the next treatment action based on the accrued information. Using existing data, a key goal is estimating the optimal regime, that, if followed by the patient population, would yield the most favorable outcome on average. Q- and A-learning are two main approaches for this purpose. We provide a detailed account of these methods, study their performance, and illustrate them using data from a depression study.