Nonparametric predictive inference for comparison of two diagnostic tests
| Autor: | Frank P. A. Coolen, Tahani Coolen-Maturi, Manal H. Alabdulhadi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
021103 operations research business.industry 0211 other engineering and technologies Nonparametric statistics Diagnostic test 02 engineering and technology Machine learning computer.software_genre 01 natural sciences 010104 statistics & probability Predictive inference Artificial intelligence 0101 mathematics business computer Mathematics |
| Zdroj: | Communications in statistics-theory and methods, 2021, Vol.50(19), pp.4470-4486 [Peer Reviewed Journal] |
| Popis: | An important aim in diagnostic medical research is comparison of the accuracy of two diagnostic tests. In this paper, comparison of two diagnostic tests is presented using nonparametric predictive inference (NPI) for future order statistics. The tests are assumed to be applied on the same individuals from two groups, e.g., healthy and diseased individuals, or from three groups with a known ordering, e.g., adding a group of severely diseased individuals to the two group scenario. Our comparison is explicitly in terms of lower and upper probabilities for proportions of correctly diagnosed future individuals from each group, for a given total number of such individuals. We include in our comparison the possibility that it is more important to get a correct diagnosis for individuals from one group than from another group. |
| Databáze: | OpenAIRE |
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