The optimal linear combination of multiple predictors under the generalized linear models

DOI10.1016/J.SPL.2009.08.002zbMath1176.62109OpenAlexW2079842414WikidataQ37409689 ScholiaQ37409689MaRDI QIDQ1036606

Hua Jin, Ying Lu

Publication date: 13 November 2009

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2772215

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (4)

Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve ⋮ Covariate-adjusted Bayesian estimation of the performance of a continuous diagnostic test with a limit of detection in the absence of a reference standard: a simulation study ⋮ On the use of min-max combination of biomarkers to maximize the partial area under the ROC curve ⋮ Evaluating the improvement in diagnostic utility from adding new predictors

Cites Work

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• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
• The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis
• Linear Combinations of Multiple Diagnostic Markers
• A regression modelling framework for receiver operating characteristic curves in medical diagnostic testing
• ROC SURFACE: A GENERALIZATION OF ROC CURVE ANALYSIS

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