Construction of confidence intervals for the maximum of the Youden index and the corresponding cutoff point of a continuous biomarker

DOI10.1002/bimj.201700107zbMath1412.62141OpenAlexW2899968271WikidataQ58575637 ScholiaQ58575637MaRDI QIDQ4626715

Leonidas E. Bantis, Benjamin Reiser, Christos T. Nakas

Publication date: 28 February 2019

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201700107

zbMATH Keywords

sensitivitysplinesconfidence intervalskernelsdelta methodROC curvespecificityYouden indexbox-Cox transformation

Mathematics Subject Classification ID

Numerical computation using splines (65D07) Parametric tolerance and confidence regions (62F25) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (3)

Statistical inference for the difference between two maximized Youden indices obtained from correlated biomarkers ⋮ Unnamed Item ⋮ Biomarker assessment in ROC curve analysis using the length of the curve as an index of diagnostic accuracy: the binormal model framework

Uses Software

• KernSmooth
• bootstrap

Cites Work

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• Survival estimation through the cumulative hazard function with monotone natural cubic splines
• Comparing two tests used for diagnostic or screening purposes
• Joint inference about sensitivity and specificity at the optimal cut-off point associated with Youden index
• Statistical Methods in Diagnostic Medicine
• Confidence Intervals for the Youden Index and Corresponding Optimal Cut-Point
• ROC Curves for Continuous Data
• Statistical Tests Based on Transformed Data
• Construction of confidence regions in the ROC space after the estimation of the optimal Youden index‐based cut‐off point
• The Youden Index and the Optimal Cut-Point Corrected for Measurement Error
• Estimation of the Youden Index and its Associated Cutoff Point
• Comparing the Areas Under Two Correlated ROC Curves: Parametric and Non‐Parametric Approaches
• Testing the difference between two Kolmogorov–Smirnov values in the context of receiver operating characteristic curves
• Smooth ROC curves and surfaces for markers subject to a limit of detection using monotone natural cubic splines

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