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All tests are imperfect: Accounting for false positives and false negatives using Bayesian statistics
Tests with binary outcomes (e.g., positive versus negative) to indicate a binary state of nature (e.g., disease agent present versus absent) are common. These tests are rarely perfect: chances of a false positive and a false negative always exist. Imperfect results cannot be directly used to infer t...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082531/ https://www.ncbi.nlm.nih.gov/pubmed/32211545 http://dx.doi.org/10.1016/j.heliyon.2020.e03571 |