Simple, efficient estimators of treatment effects in randomized trials using generalized linear models to leverage baseline variables

DOI10.2202/1557-4679.1138zbMATH Open1548.62182WikidataQ53070668 ScholiaQ53070668MaRDI QIDQ6644599

Michael Rosenblum, Mark J. Van der Laan

Publication date: 27 November 2024

Published in: The International Journal of Biostatistics (Search for Journal in Brave)

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (5)

Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates ⋮ Machine learning methods for leveraging baseline covariate information to improve the efficiency of clinical trials ⋮ Defining and estimating effects in cluster randomized trials: a methods comparison ⋮ Designing efficient randomized trials: power and sample size calculation when using semiparametric efficient estimators ⋮ Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score

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