Doubly Robust Estimation of Optimal Dosing Strategies

• 成果类型: Article
• 署名作者: Schulz, Juliana; Moodie, Erica E. M.
• 署名单位: Universite de Montreal; HEC Montreal; McGill University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2020.1753521
• 发表日期: 2021
• 页码: 256-268
• 关键词: propensity score; Causal Inference; warfarin

摘要

The goal of precision medicine is to tailor treatment strategies on an individual patient level. Although several estimation techniques have been developed for determining optimal treatment rules, the majority of methods focus on the case of a dichotomous treatment, an example being the dynamic weighted ordinary least squares regression approach of Wallace and Moodie. We propose an extension to the aforementioned framework to allow for a continuous treatment with the ultimate goal of estimating optimal dosing strategies. The proposed method is shown to be doubly robust against model misspecification whenever the implemented weights satisfy a particular balancing condition. A broad class of weight functions can be derived from the balancing condition, providing a flexible regression based estimation method in the context of adaptive treatment strategies for continuous valued treatments. for this article are available online.