Machine learning methods for leveraging baseline covariate information to improve the efficiency of clinical trials

DOI10.1002/sim.8054zbMATH Open1545.62685WikidataQ93358578 ScholiaQ93358578MaRDI QIDQ6625579

Zhiwei Zhang, Shujie Ma

Publication date: 28 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

augmentationasymptotic efficiencyinfluence functioncross-validationsuper learnersemiparametric theory

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
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• Asymptotic Statistics
• Regularization and Variable Selection Via the Elastic Net
• Super Learner
• Random forests
• The Elements of Statistical Learning
• Empirical efficiency maximization: improved locally efficient covariate adjustment in randomized experiments and survival analysis
• Simple, efficient estimators of treatment effects in randomized trials using generalized linear models to leverage baseline variables

Related Items (2)

Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates ⋮ Designing efficient randomized trials: power and sample size calculation when using semiparametric efficient estimators

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