ArticleThe international journal of biostatistics2016
Optimal Individualized Treatments in Resource-Limited Settings.
Article in The international journal of biostatistics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial.JAMA psychiatry · 2023Trial
- Machine learning for estimating and comparing clinical rules for treating diarrheal illness with antibiotics.medRxiv : the preprint server for health sciences · 2025Article
- Estimating heterogeneous impacts Of subsidised health insurance: A causal machine learning approach.PloS one · 2025Article
- Learning optimal dynamic treatment regimes from longitudinal data.American journal of epidemiology · 2024Article
- The optimal dynamic treatment rule superlearner: considerations, performance, and application to criminal justice interventions.The international journal of biostatistics · 2023Article
- Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine-Learning Approach in the MESA Study.Circulation · 2023Article
- Targeted Search for Individualized Clinical Decision Rules to Optimize Clinical Outcomes.Statistics in biosciences · 2022Article
- Individualized treatment rules under stochastic treatment cost constraints.Journal of causal inference · 2022Article
- Estimating optimal dynamic treatment strategies under resource constraints using dynamic marginal structural models.Statistics in medicine · 2021Article
- Optimal individualized decision rules using instrumental variable methods.Journal of the American Statistical Association · 2021Article
- Rejoinder: Optimal individualized decision rules using instrumental variable methods.Journal of the American Statistical Association · 2021Article
- Direct and indirect effects of marijuana use on the risk of fatal 2-vehicle crash initiation.Injury epidemiology · 2020Article
- Learning-based biomarker-assisted rules for optimized clinical benefit under a risk constraint.Biometrics · 2020Article
- Re. Selecting Optimal Subgroups for Treatment Using Many Covariates.Epidemiology (Cambridge, Mass.) · 2020Article
- Bayesian Nonparametric Policy Search with Application to Periodontal Recall Intervals.Journal of the American Statistical Association · 2020Article
- Suicide prediction models: a critical review of recent research with recommendations for the way forward.Molecular psychiatry · 2020Review
- The Interaction Continuum.Epidemiology (Cambridge, Mass.) · 2019Review
- Selecting Optimal Subgroups for Treatment Using Many Covariates.Epidemiology (Cambridge, Mass.) · 2019Article
- Precision Medicine.Annual review of statistics and its application · 2019Article
- Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects.BMJ (Clinical research ed.) · 2018Review
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2 authors.
Funding
Abstract
An individualized treatment rule (ITR) is a treatment rule which assigns treatments to individuals based on (a subset of) their measured covariates. An optimal ITR is the ITR which maximizes the population mean outcome. Previous works in this area have assumed that treatment is an unlimited resource so that the entire population can be treated if this strategy maximizes the population mean outcome. We consider optimal ITRs in settings where the treatment resource is limited so that there is a maximum proportion of the population which can be treated. We give a general closed-form expression for an optimal stochastic ITR in this resource-limited setting, and a closed-form expression for the optimal deterministic ITR under an additional assumption. We also present an estimator of the mean outcome under the optimal stochastic ITR in a large semiparametric model that at most places restrictions on the probability of treatment assignment given covariates. We give conditions under which our estimator is efficient among all regular and asymptotically linear estimators. All of our results are supported by simulations.
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Registered trials
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.