ArticleJournal of the American Statistical Association2021
Optimal individualized decision rules using instrumental variable methods.
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. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Internet-delivered cognitive behavior therapy versus treatment as usual for anxiety and depression among Latin American university students: A randomized clinical trial.Journal of consulting and clinical psychology · 2023Trial
- 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
- A non-parametric Bayesian approach for adjusting partial compliance in sequential decision making.Statistics in medicine · 2023Trial
- Challenges and opportunities in biomarker-driven trials: adaptive randomization.Annals of translational medicine · 2022Trial
- Developing an individualized treatment rule for Veterans with major depressive disorder using electronic health records.Molecular psychiatry · 2024Article
- 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
- Nonparametric Bayesian Q-learning for optimization of dynamic treatment regimes in the presence of partial compliance.Statistical methods in medical research · 2023Article
- Monte Carlo sensitivity analysis for unmeasured confounding in dynamic treatment regimes.Biometrical journal. Biometrische Zeitschrift · 2023Observational
- Accountable survival contrast-learning for optimal dynamic treatment regimes.Scientific reports · 2023Article
- 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
- Meta-analysis of individualized treatment rules via sign-coherency.Proceedings of machine learning research · 2022Article
- Estimation in regret-regression using quadratic inference functions with ridge estimator.PloS one · 2022Article
- Individualized treatment rules under stochastic treatment cost constraints.Journal of causal inference · 2022Article
- Correction to: "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
- Machine intelligence for individualized decision making under a counterfactual world: A rejoinder.Journal of the American Statistical Association · 2021Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
There is an extensive literature on the estimation and evaluation of optimal individualized treatment rules in settings where all confounders of the effect of treatment on outcome are observed. We study the development of individualized decision rules in settings where some of these confounders may not have been measured but a valid binary instrument is available for a binary treatment. We first consider individualized treatment rules, which will naturally be most interesting in settings where it is feasible to intervene directly on treatment. We then consider a setting where intervening on treatment is infeasible, but intervening to encourage treatment is feasible. In both of these settings, we also handle the case that the treatment is a limited resource so that optimal interventions focus the available resources on those individuals who will benefit most from treatment. Given a reference rule, we evaluate an optimal individualized rule by its average causal effect relative to a prespecified reference rule. We develop methods to estimate optimal individualized rules and construct asymptotically efficient plug-in estimators of the corresponding average causal effect relative to a prespecified reference rule.
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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.