Three-group ROC predictive analysis for ordinal outcomes

Coolen-Maturi, T.

doi:10.1080/03610926.2016.1212074

Three-group ROC predictive analysis for ordinal outcomes

Coolen-Maturi, T.

Authors

Dr Tahani Coolen-Maturi tahani.maturi@durham.ac.uk
Associate Professor

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

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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in Communications in statistics : theory and methods on 12/09/2016, available online at: http://www.tandfonline.com/10.1080/03610926.2016.1212074.