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Three-group ROC analysis : a nonparametric predictive approach.

Coolen-Maturi, T. and Elkhafifi, F.F. and Coolen, F.P.A. (2014) 'Three-group ROC analysis : a nonparametric predictive approach.', Computational statistics & data analysis., 78 . pp. 69-81.

Abstract

Measuring the accuracy of diagnostic tests is crucial in many application areas, in particular medicine and health care. 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. Nonparametric predictive inference (NPI) is a frequentist statistical method that is explicitly aimed at using few modelling assumptions in addition to data, enabled through the use of lower and upper probabilities to quantify uncertainty. It focuses exclusively on a future observation, which may be particularly relevant if one considers decisions about a diagnostic test to be applied to a future patient. The NPI approach to three-group ROC analysis is presented, including results on the volumes under the ROC surfaces and choice of decision threshold for the diagnosis.

Item Type:Article
Keywords:Diagnostic accuracy, Lower and upper probability, Nonparametric predictive inference, Receiver operating characteristic (ROC) surface, Youden’s index.
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1016/j.csda.2014.04.005
Publisher statement:NOTICE: this is the author’s version of a work that was accepted for publication in Computational Statistics & Data Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computational Statistics & Data Analysis, 78, 2014, 10.1016/j.csda.2014.04.005.
Record Created:04 Jun 2014 10:05
Last Modified:05 Jun 2014 13:40

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