ci_clus_vus

Computes confidence intervals for covariate-specific 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.

Duc-Khanh To

ClusROC

ROC Analysis in Three-Class Classification Problems for
Clustered Data

Gianfranco Adimari

Monica Chiogna

ci_clus_vus function

<dl><dt>x</dt>
<dd>an object of class "VUS", a result of <code>clus_vus</code> call.</dd>
<dt>ci_level</dt>
<dd>a confidence level to be used for constructing the confidence interval; default is 0.95.</dd></dl>

Arguments

Confidence Intervals for Covariate-specific VUS — ci_clus_vus

<dl>

<dt>x</dt>
<dd>an object of class "VUS", a result of <code>clus_vus</code> call.</dd>


<dt>ci_level</dt>
<dd>a confidence level to be used for constructing the confidence interval; default is 0.95.</dd>

</dl>

ci_clus_vus: Confidence Intervals for Covariate-specific VUS

Description

Usage

Value

Arguments

Details

See Also