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...

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Detalles Bibliográficos
Autores principales: Qian, Song S., Refsnider, Jeanine M., Moore, Jennifer A., Kramer, Gunnar R., Streby, Henry M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Article
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

Internet

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

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