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.
- Version1.0.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- To et al. (2022)
- Xiong et al. (2018)
- Last release11/17/2022
Documentation
Team
Duc-Khanh To
Gianfranco Adimari
Monica Chiogna
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- Depends2 packages
- Imports8 packages
- Suggests1 package
- Linking To2 packages