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.">

ClusROC: ROC Analysis in Three-Class Classification Problems for Clustered Data (original) (raw)

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: 1.0.3
Depends: R (≥ 3.5.0), stats, utils, graphics, nlme, Rcpp (≥ 0.12.3)
Imports: rgl, ellipse, numDeriv, ggplot2, ggpubr, foreach, iterators, parallel, doParallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0)
Published: 2025-10-01
DOI: 10.32614/CRAN.package.ClusROC
Author: Duc-Khanh To ORCID iD [aut, cre], Gianfranco Adimari [ctb], Monica Chiogna [ctb]
Maintainer: Duc-Khanh To
BugReports: https://github.com/toduckhanh/ClusROC/issues
License: GPL-3
URL: https://github.com/toduckhanh/ClusROC
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: ClusROC results

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