ArticleJournal of the American Statistical Association2021
Improved doubly robust estimation in learning optimal individualized treatment rules.
Article in Journal of the American Statistical Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Challenges and opportunities in biomarker-driven trials: adaptive randomization.Annals of translational medicine · 2022Trial
- Authors' reply to the Discussion of 'Methods for estimating the exposure-response curve to inform the new safety standards for fine particulate matter'.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- A Simple Diagnostic for the Positivity Assumption for Continuous Exposures.Statistics in medicine · 2025Article
- Methods for Estimating the Exposure-Response Curve to Inform the New Safety Standards for Fine Particulate Matter.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- Dynamic Treatment Regimes on Dyadic Networks.Statistics in medicine · 2024Article
- Variable selection in high dimensions for discrete-outcome individualized treatment rules: Reducing severity of depression symptoms.Biostatistics (Oxford, England) · 2024Article
- Variable selection for individualised treatment rules with discrete outcomes.Journal of the Royal Statistical Society. Series C, Applied statistics · 2024Article
- A RELUCTANT ADDITIVE MODEL FRAMEWORK FOR INTERPRETABLE NONLINEAR INDIVIDUALIZED TREATMENT RULES.The annals of applied statistics · 2023Article
- Bayesian Sequential Design for Identifying and Ranking Effective Patient Subgroups in Precision Medicine in the Case of Counting Outcome Data with Inflated Zeros.Journal of personalized medicine · 2023Article
- Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments.Journal of machine learning research : JMLR · 2023Article
- Privacy-preserving estimation of an optimal individualized treatment rule: a case study in maximizing time to severe depression-related outcomes.Lifetime data analysis · 2022Article
- Evaluating the heterogeneous effect of a modifiable risk factor on suicide: The case of vitamin D deficiency.International journal of methods in psychiatric research · 2022Observational
- Multithreshold change plane model: Estimation theory and applications in subgroup identification.Statistics in medicine · 2021Article
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2 authors.
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Abstract
Individualized treatment rules (ITRs) recommend treatment according to patient characteristics. There is a growing interest in developing novel and efficient statistical methods in constructing ITRs. We propose an improved doubly robust estimator of the optimal ITRs. The proposed estimator is based on a direct optimization of an augmented inverse-probability weighted estimator (AIPWE) of the expected clinical outcome over a class of ITRs. The method enjoys two key properties. First, it is doubly robust, meaning that the proposed estimator is consistent when either the propensity score or the outcome model is correct. Second, it achieves the smallest variance among the class of doubly robust estimators when the propensity score model is correctly specified, regardless of the specification of the outcome model. Simulation studies show that the estimated ITRs obtained from our method yield better results than those obtained from current popular methods. Data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is analyzed as an illustrative example.
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