A Shrinkage Approach for Estimating a Treatment Effect Using Intermediate Biomarker Data in Clinical Trials

DOI10.1111/J.1541-0420.2011.01608.XzbMath1274.62818OpenAlexW2081091982WikidataQ33917331 ScholiaQ33917331MaRDI QIDQ2893404

Yun Li, Roderick J. A. Little

Publication date: 20 June 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3365575

zbMATH Keywords

ridge regressionauxiliary variablemissing databiomarkerrandomized trials

Mathematics Subject Classification ID

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

Related Items (3)

Improving efficiency in clinical trials using auxiliary information: Application of a multi‐state cure model ⋮ Bias reduction using surrogate endpoints as auxiliary variables ⋮ Landmark estimation of survival and treatment effects in observational studies

Cites Work

• Survival Analysis Using Auxiliary Variables Via Multiple Imputation, with Application to AIDS Clinical Trial Data
• A Measure of the Proportion of Treatment Effect Explained by a Surrogate Marker
• Nonparametric Survival Estimation Using Prognostic Longitudinal Covariates
• The validation of surrogate endpoints in meta-analyses of randomized experiments
• Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models
• Criteria for the Validation of Surrogate Endpoints in Randomized Experiments
• Properties of A Nonparametric Test for Early Comparison of Treatments in Clinical Trials in the Presence of Surrogate Endpoints
• A Generalization of Sampling Without Replacement From a Finite Universe
• Some comments on efficiency gains from auxiliary information for right-censored data

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