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Durham University

Department of Mathematical Sciences

Academic Staff

Publication details for Tahani Coolen-Maturi

Coolen-Maturi, T. (2017). Three-group ROC predictive analysis for ordinal outcomes. Communications in Statistics – Theory and Methods 46(19): 9476-9493.

Author(s) from Durham

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.