Estimation and evaluation of individualized treatment rules following multiple imputation
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Publication:6626955
DOI10.1002/SIM.9857zbMATH Open1548.62432MaRDI QIDQ6626955
Rebecca Hubbard, Jenny Shen, Kristin A. Linn
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
missing datamultiple imputationindividualized treatment ruleprecision medicinedynamic treatment regime
Cites Work
- Title not available (Why is that?)
- Doubly Robust Estimation in Missing Data and Causal Inference Models
- Sequential Advantage Selection for Optimal Treatment Regimes
- Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy
- Dynamic treatment regimes: technical challenges and applications
- Rejoinder of ``Dynamic treatment regimes: technical challenges and applications
- Generalized random forests
- Model selection and model averaging after multiple imputation
- Using decision lists to construct interpretable and parsimonious treatment regimes
- Inference for optimal dynamic treatment regimes using an adaptive \(m\)-out-of-\(n\) bootstrap scheme
- Adaptive Confidence Intervals for the Test Error in Classification
- An Algorithm for Generating Individualized Treatment Decision Trees and Random Forests
- Tree-based methods for individualized treatment regimes
- Marginal Mean Models for Dynamic Regimes
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- Statistical Analysis with Missing Data, Third Edition
- Optimal Dynamic Treatment Regimes
- Multiple Imputation for Interval Estimation From Simple Random Samples With Ignorable Nonresponse
- Generating missing values for simulation purposes: a multivariate amputation procedure
- Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials
- A stable and more efficient doubly robust estimator
- Estimating Optimal Dynamic Treatment Regimes With Survival Outcomes
- Entropy Learning for Dynamic Treatment Regimes
- Identification of the optimal treatment regimen in the presence of missing covariates
- Accounting for not-at-random missingness through imputation stacking
- Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness
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