ArticleElectronic journal of statistics2014
Dynamic treatment regimes: technical challenges and applications.
Article in Electronic journal of statistics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
66 citing papers in PubMed.
- Deeply Tailored Adaptive Interventions to Reduce College Student Drinking: a Real-World Application of Q-Learning for SMART Studies.Prevention science : the official journal of the Society for Prevention Research · 2022Trial
- Effects of a continuous nursing care model on elderly patients with total hip arthroplasty: a randomized controlled trial.Aging clinical and experimental research · 2022Trial
- Optimizing delivery of a behavioral pain intervention in cancer patients using a sequential multiple assignment randomized trial SMART.Contemporary clinical trials · 2017Trial
- Article
- Replicable Bandits for Digital Health Interventions.Statistical science : a review journal of the Institute of Mathematical Statistics · 2025Article
- Sparse 2-stage Bayesian meta-analysis for individualized treatments.Biometrics · 2025Article
- Simultaneous Feature Selection for Optimal Dynamic Treatment Regimens.Statistics in medicine · 2025Article
- Treatment heterogeneity of water, sanitation, hygiene, and nutrition interventions on child growth by environmental enteric dysfunction and pathogen status for young children in Bangladesh.PLoS neglected tropical diseases · 2025Article
- Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data.Journal of machine learning research : JMLR · 2025Article
- Estimating optimal decision trees for treatment assignment: The case of K > 2 treatment alternatives.Behavior research methods · 2024Article
- Adaptive randomization methods for sequential multiple assignment randomized trials (smarts) via thompson sampling.Biometrics · 2024Article
- Estimating individualized treatment rules by optimizing the adjusted probability of a longer survival.Statistical methods in medical research · 2024Article
- A MARGINAL STRUCTURAL MODEL FOR PARTIAL COMPLIANCE IN SMARTS.The annals of applied statistics · 2024Article
- Treatment Heterogeneity of Water, Sanitation, Hygiene, and Nutrition Interventions on Child Growth by Environmental Enteric Dysfunction and Pathogen Status for Young Children in Bangladesh.medRxiv : the preprint server for health sciences · 2024Article
- Modified interactive Q-learning for attenuating the impact of model misspecification with treatment effect heterogeneity.Statistical methods in medical research · 2023Article
- Outcome trajectory estimation for optimal dynamic treatment regimes with repeated measures.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023Article
- Monte Carlo sensitivity analysis for unmeasured confounding in dynamic treatment regimes.Biometrical journal. Biometrische Zeitschrift · 2023Observational
- Using Pilot Data for Power Analysis of Observational Studies for the Estimation of Dynamic Treatment Regimes.Observational studies · 2023Article
- Semi-Supervised Off-Policy Reinforcement Learning and Value Estimation for Dynamic Treatment Regimes.Journal of machine learning research : JMLR · 2023Article
- BATCH POLICY LEARNING IN AVERAGE REWARD MARKOV DECISION PROCESSES.Annals of statistics · 2022Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Dynamic treatment regimes are of growing interest across the clinical sciences because these regimes provide one way to operationalize and thus inform sequential personalized clinical decision making. Formally, a dynamic treatment regime is a sequence of decision rules, one per stage of clinical intervention. Each decision rule maps up-to-date patient information to a recommended treatment. We briefly review a variety of approaches for using data to construct the decision rules. We then review a critical inferential challenge that results from nonregularity, which often arises in this area. In particular, nonregularity arises in inference for parameters in the optimal dynamic treatment regime; the asymptotic, limiting, distribution of estimators are sensitive to local perturbations. We propose and evaluate a locally consistent Adaptive Confidence Interval (ACI) for the parameters of the optimal dynamic treatment regime. We use data from the Adaptive Pharmacological and Behavioral Treatments for Children with ADHD Trial as an illustrative example. We conclude by highlighting and discussing emerging theoretical problems in this area.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.