A Framework for Random-Effects ROC Analysis: Biases with the Bootstrap and Other Variance Estimators

DOI10.1080/03610920802610084zbMath1170.62038OpenAlexW2144993136MaRDI QIDQ114169

Robert F. Wagner, Brandon Gallas, Andriy Bandos, Frank W. Samuelson, Brandon D. Gallas, Andriy I. Bandos, Robert F. Wagner, Frank W. Samuelson

Publication date: 23 July 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802610084

zbMATH Keywords

biasWilcoxon-Mann-Whitney statisticROC analysismulti-reader multi-case (MRMC)nonparametric AUCthree-way bootstrap

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Design of statistical experiments (62K99) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09) Biomedical imaging and signal processing (92C55)

Related Items (2)

Classifier variability: accounting for training and testing ⋮ iMRMC

Cites Work

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• Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests an anova approach with dependent observations
• Exact Bootstrap Variances of the Area Under ROC Curve
• A marginal model approach for analysis of multi-reader multi-test receiver operating characteristic (ROC) data

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