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Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals.

Alabdulhadi, M.H. and Coolen, F.P.A. and Coolen-Maturi, T. (2019) 'Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals.', Journal of statistical theory and practice., 13 . p. 38.

Abstract

In clinical applications, it is important to compare and study the ability of diagnostic tests to discriminate between individuals with and without the disease. In this paper, comparison of two diagnostic tests is presented and discussed using nonparametric predictive inference (NPI). We compare the two tests by considering the total numbers of correct diagnoses for specific numbers of future healthy individuals and future patients. This NPI approach for comparison of diagnostic tests is also generalized by the use of weighted sums for the healthy and patients groups, reflecting possibly different importance of correct diagnoses. Examples are provided to illustrate the new method.

Item Type:Article
Full text:Publisher-imposed embargo
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1007/s42519-019-0039-6
Publisher statement:© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Date accepted:20 February 2019
Date deposited:06 March 2019
Date of first online publication:14 March 2019
Date first made open access:No date available

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