ROC Analysis in Three-Class Classification Problems for Clustered Data
Confidence Intervals for Covariate-specific VUS
Linear Mixed-Effects Models for a continuous diagnostic test or a biom...
Estimation of the covariate-specific optimal pair of thresholds for cl...
Plot an estimated covariate-specific ROC surface for clustered data.
Estimation of the covariate-specific TCFs for clustered data.
Estimation of the covariate-specific VUS for clustered data.
ROC Analysis in Three-Class Classification Problems for Clustered Data
Plot an clus_lme object.
Plot of confidence regions for covariate-specific optimal pair of thre...
Print summary results from ci_clus_vus
Print summary results of an clus_lme object
Print summary results from clus_opt_thres3
Print summary results from clus_tcfs
Print summary results from clus_vus
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.