Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve

DOI10.1016/j.csda.2014.12.002zbMath1470.62024OpenAlexW1986550724MaRDI QIDQ1663274

Taesung Park, WenBao Yu

Publication date: 21 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.12.002

zbMATH Keywords

linear combinationbiomarkersdiagnostic accuracypartial area under ROC curve (pAUC)receive operating characteristic (ROC) curve

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Combining biomarkers by maximizing the true positive rate for a fixed false positive rate ⋮ On the use of min-max combination of biomarkers to maximize the partial area under the ROC curve

Uses Software

• copula
• pROC
• copula

Cites Work

• A modified area under the ROC curve and its application to marker selection and classification
• The optimal linear combination of multiple predictors under the generalized linear models
• The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
• Partial AUC maximization in a linear combination of dichotomizers
• Selecting Differentially Expressed Genes from Microarray Experiments
• Partial AUC Estimation and Regression
• Marker selection via maximizing the partial area under the ROC curve of linear risk scores
• Semiparametric and parametric transformation models for comparing diagnostic markers with paired design
• A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
• The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis
• Linear Combinations of Multiple Diagnostic Markers
• Combining diagnostic test results to increase accuracy
• Semi-parametric estimation of the binormal ROC curve for a continuous diagnostic test

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