ClusROC: ROC Analysis in Three-Class Classification Problems for Clustered Data

Statistical methods for ROC surface analysis in three-class classification problems for clustered data and in presence of covariates. In particular, the package allows to obtain covariate-specific point and interval estimation for: (i) true class fractions (TCFs) at fixed pairs of thresholds; (ii) the ROC surface; (iii) the volume under ROC surface (VUS); (iv) the optimal pairs of thresholds. Methods considered in points (i), (ii) and (iv) are proposed and discussed in To et al. (2022) <doi:10.1177/09622802221089029>. Referring to point (iv), three different selection criteria are implemented: Generalized Youden Index (GYI), Closest to Perfection (CtP) and Maximum Volume (MV). Methods considered in point (iii) are proposed and discussed in Xiong et al. (2018) <doi:10.1177/0962280217742539>. Visualization tools are also provided. We refer readers to the articles cited above for all details.

Version: 1.0.1
Depends: R (≥ 3.5.0), stats, utils, graphics, nlme
Imports: rgl, car, numDeriv, ggplot2, ggpubr, snow, doSNOW, foreach
Published: 2022-05-25
Author: Duc-Khanh To [aut, cre] (<>), with contributions from Gianfranco Adimari and Monica Chiogna
Maintainer: Duc-Khanh To <toduc at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: ClusROC results


Reference manual: ClusROC.pdf


Package source: ClusROC_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ClusROC_1.0.1.tgz, r-oldrel (arm64): ClusROC_1.0.1.tgz, r-release (x86_64): ClusROC_1.0.1.tgz, r-oldrel (x86_64): ClusROC_1.0.1.tgz


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