ROC Analyses Based on Measuring Evidence
Applications
2021-03-02 v1 Methodology
Abstract
ROC analyses are considered under a variety of assumptions concerning the distributions of a measurement in two populations. These include the binormal model as well as nonparametric models where little is assumed about the form of distributions. The methodology is based on a characterization of statistical evidence which is dependent on the specification of prior distributions for the unknown population distributions as well as for the relevant prevalence of the disease in a given population. In all cases, elicitation algorithms are provided to guide the selection of the priors. Inferences are derived for the AUC as well as the cutoff used for classification and the associated error characteristics.
Keywords
Cite
@article{arxiv.2103.00772,
title = {ROC Analyses Based on Measuring Evidence},
author = {Luai Al Labadi and Michael Evans and Qiaoyu Liang},
journal= {arXiv preprint arXiv:2103.00772},
year = {2021}
}