ArticleJournal of the American Statistical Association2020
Multi-Armed Angle-Based Direct Learning for Estimating Optimal Individualized Treatment Rules With Various Outcomes.
Article in Journal of the American Statistical Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Variable selection for estimating optimal treatment regimes with multiple treatments.Scientific reports · 2026Article
- Robust transfer learning for individualized treatment rules in the presence of missing data.Biostatistics (Oxford, England) · 2025Article
- Deep learning-based ranking method for subgroup and predictive biomarker identification in patients.Communications medicine · 2025Article
- Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection.Journal of machine learning research : JMLR · 2025Article
- A Simple Nonparametric Least-Squares-Based Causal Inference for Heterogeneous Treatment Effects.Journal of nonparametric statistics · 2025Article
- Penalized robust learning for optimal treatment regimes with heterogeneous individualized treatment effects.Journal of applied statistics · 2024Article
- Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls.Journal of machine learning research : JMLR · 2024Article
- A RELUCTANT ADDITIVE MODEL FRAMEWORK FOR INTERPRETABLE NONLINEAR INDIVIDUALIZED TREATMENT RULES.The annals of applied statistics · 2023Article
- A reference-free R-learner for treatment recommendation.Statistical methods in medical research · 2023Article
- Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments.Journal of machine learning research : JMLR · 2023Article
- Meta-analysis of individualized treatment rules via sign-coherency.Proceedings of machine learning research · 2022Article
- Learning Optimal Distributionally Robust Individualized Treatment Rules.Journal of the American Statistical Association · 2021Article
- A semiparametric instrumental variable approach to optimal treatment regimes under endogeneity.Journal of the American Statistical Association · 2021Article
- Estimation and Validation of Ratio-based Conditional Average Treatment Effects Using Observational Data.Journal of the American Statistical Association · 2021Article
- Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness.Statistics in medicine · 2020Article
- Near-optimal Individualized Treatment Recommendations.Journal of machine learning research : JMLR · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Estimating an optimal individualized treatment rule (ITR) based on patients' information is an important problem in precision medicine. An optimal ITR is a decision function that optimizes patients' expected clinical outcomes. Many existing methods in the literature are designed for binary treatment settings with the interest of a continuous outcome. Much less work has been done on estimating optimal ITRs in multiple treatment settings with good interpretations. In this article, we propose angle-based direct learning (AD-learning) to efficiently estimate optimal ITRs with multiple treatments. Our proposed method can be applied to various types of outcomes, such as continuous, survival, or binary outcomes. Moreover, it has an interesting geometric interpretation on the effect of different treatments for each individual patient, which can help doctors and patients make better decisions. Finite sample error bounds have been established to provide a theoretical guarantee for AD-learning. Finally, we demonstrate the superior performance of our method via an extensive simulation study and real data applications. Supplementary materials for this article are available online.
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