Bayesian latent class analysis produced diagnostic accuracy estimates that were more interpretable than composite reference standards for extrapulmonary tuberculosis tests

BACKGROUND: Evaluating the accuracy of extrapulmonary tuberculosis (TB) tests is challenging due to lack of a gold standard. Latent class analysis (LCA), a statistical modeling approach, can adjust for reference tests’ imperfect accuracies to produce less biased test accuracy estimates than those pr...

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Detalles Bibliográficos
Autores principales: MacLean, Emily L., Kohli, Mikashmi, Köppel, Lisa, Schiller, Ian, Sharma, Surendra K., Pai, Madhukar, Denkinger, Claudia M., Dendukuri, Nandini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202094/
https://www.ncbi.nlm.nih.gov/pubmed/35706064
http://dx.doi.org/10.1186/s41512-022-00125-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202094/
https://www.ncbi.nlm.nih.gov/pubmed/35706064
http://dx.doi.org/10.1186/s41512-022-00125-x

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