Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates

DOI10.1214/18-AOAS1154zbMath1412.62189OpenAlexW2901231506WikidataQ128948407 ScholiaQ128948407MaRDI QIDQ1728653

Baqun Zhang, Min Zhang

Publication date: 25 February 2019

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1542078047

zbMATH Keywords

classificationhigh-dimensional datavariable selectionmisclassification errorpersonalized medicineC-learningdynamic treatment regime

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (3)

Subgroup identification and variable selection for treatment decision making ⋮ Efficient screening of predictive biomarkers for individual treatment selection ⋮ Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates

Uses Software

• rgenoud

Cites Work

• Unnamed Item
• Doubly Robust Estimation in Missing Data and Causal Inference Models
• Sequential Advantage Selection for Optimal Treatment Regimes
• \(Q\)- and \(A\)-learning methods for estimating optimal dynamic treatment regimes
• Performance guarantees for individualized treatment rules
• Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates
• \({\mathcal Q}\)-learning
• Combining biomarkers to optimize patient treatment recommendations
• A Generalized Estimator of the Attributable Benefit of an Optimal Treatment Regime
• Estimating Individualized Treatment Rules Using Outcome Weighted Learning
• Optimal Dynamic Treatment Regimes
• A Robust Method for Estimating Optimal Treatment Regimes
• A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
• Inference for non-regular parameters in optimal dynamic treatment regimes
• Optimal Structural Nested Models for Optimal Sequential Decisions
• New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
• Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions
• Demystifying Optimal Dynamic Treatment Regimes

This page was built for publication: Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates