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: 1.0.2 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: 2022-11-17 DOI: 10.32614/CRAN.package.ClusROC Author: Duc-Khanh To [aut, cre] (<https://orcid.org/0000-0002-4641-0764>), with contributions from Gianfranco Adimari and Monica Chiogna Maintainer: Duc-Khanh To <toduc at stat.unipd.it> 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=ClusROC to link to this page.
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