Comparing Three-class Diagnostic Tests by Three-way ROC Analysis
Stephan Dreiseitl,
Lucila Ohno-Machado and
Michael Binder
Medical Decision Making, 2000, vol. 20, issue 3, 323-331
Abstract:
Three-way ROC surfaces are based on a generalization of dichotomous ROC analysis to three-class diagnostic tests. The discriminatory power of three-class diagnostic tests is measured by the volume under the ROC surface. This measure can be given a probabilistic interpretation similar to the equivalence of the c-index to the area under the ROC curve. This article presents a method to calculate nonparametric estimates of the variance of the volume under the surface using Mann-Whitney U statistics. As a simple extension of this result, it is possible to calculate covariance estimates for the volume under the surface. This allows the statistical comparison of two tests used for diagnostic tasks with three possible outcomes. The formulas derived are validated on synthetic data and applied to a three-class data set of pigmented skin lesions. It is shown that a neural network algorithm trained on clinical data and lesion features performs better than one trained on only the lesion features. Key words: Receiver operating characteristic curves; trichotomous ROC analysis. (Med Decis Making 2000; 20:323-331)
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X0002000309 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:20:y:2000:i:3:p:323-331
DOI: 10.1177/0272989X0002000309
Access Statistics for this article
More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().