Nonparametric predictive comparison of two diagnostic tests based on total numbers of correctly diagnosed individuals
Alabdulhadi, M.H.; Coolen, F.P.A.; Coolen-Maturi, T.
Professor Frank Coolen firstname.lastname@example.org
Dr Tahani Coolen-Maturi email@example.com
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.
Alabdulhadi, M., Coolen, F., & 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, Article 38. https://doi.org/10.1007/s42519-019-0039-6
|Journal Article Type||Article|
|Acceptance Date||Feb 20, 2019|
|Online Publication Date||Mar 14, 2019|
|Publication Date||Sep 30, 2019|
|Deposit Date||Feb 22, 2019|
|Publicly Available Date||Mar 15, 2019|
|Journal||Journal of Statistical Theory and Practice|
|Peer Reviewed||Peer Reviewed|
Published Journal Article
Publisher Licence URL
© 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.
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