Combining Multiple Biomarker Models in Logistic Regression

DOI10.1111/j.1541-0420.2007.00904.xzbMath1137.62404OpenAlexW2015902483WikidataQ51891478 ScholiaQ51891478MaRDI QIDQ3506487

Debashis Ghosh, Zheng Yuan

Publication date: 13 June 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc7092376

zbMATH Keywords

classificationgeneralized degrees of freedomreceiver operating characteristic curvediagnostic tests

Mathematics Subject Classification ID

Related Items (8)

The likelihood approach for the comparison of medical diagnostic system with multiple binary tests ⋮ A resample-replace lasso procedure for combining high-dimensional markers with limit of detection ⋮ Estimation for volunteer web survey samples using a model-averaging approach ⋮ Matrix variate receiver operating characteristic curve for binary classification ⋮ Adaptively combined forecasting for discrete response time series ⋮ An improved model averaging scheme for logistic regression ⋮ Sparsity Oriented Importance Learning for High-Dimensional Linear Regression ⋮ The use of components’ weights improves the diagnostic accuracy of a health-related index

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• Linear Combinations of Multiple Diagnostic Markers
• Adaptive Regression by Mixing
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• Optimal Sample Size for Multiple Testing
• Combining biomarkers to detect disease with application to prostate cancer
• Combining Linear Regression Models

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