Three-group ROC predictive analysis for ordinal outcomes

Coolen-Maturi, T.

Abstract

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) surface is a useful tool to assess the ability of a diagnostic test to discriminate among three ordered classes or groups. In this paper, nonparametric predictive inference (NPI) for three-group ROC analysis for ordinal outcomes is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. This paper also includes results on the volumes under the ROC surfaces and consideration of the choice of decision thresholds for the diagnosis. Two examples are provided to illustrate our method.

Citation

Coolen-Maturi, T. (2016). Three-group ROC predictive analysis for ordinal outcomes. Communications in Statistics - Theory and Methods, 46(19), 9476--9493. https://doi.org/10.1080/03610926.2016.1212074

• Journal Article Type: Article
• Acceptance Date: Jul 7, 2016
• Online Publication Date: Sep 12, 2016
• Publication Date: Sep 12, 2016
• Deposit Date: Jul 20, 2016
• Publicly Available Date: Sep 12, 2017
• Journal: Communications in Statistics - Theory and Methods
• Print ISSN: 0361-0926
• Electronic ISSN: 1532-415X
• Publisher: Taylor and Francis Group
• Peer Reviewed: Peer Reviewed
• Volume: 46
• Issue: 19
• Pages: 9476--9493
• DOI: https://doi.org/10.1080/03610926.2016.1212074
• Public URL: https://durham-repository.worktribe.com/output/1400665