toduckhanh/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.
Getting started
Browse package contents
Package details |
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| 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@stat.unipd.it> |
| License | GPL-3 |
| Version | 1.0.2 |
| URL | https://github.com/toduckhanh/ClusROC |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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