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Estimating prevalence and test accuracy in disease ecology: How Bayesian latent class analysis can boost or bias imperfect test results
1. Obtaining accurate estimates of disease prevalence is crucial for the monitoring and management of wildlife populations but can be difficult if different diagnostic tests yield conflicting results and if the accuracy of each diagnostic test is unknown. Bayesian latent class analysis (BLCA) modeli...
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| Pubblicato in: | Ecol Evol |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
John Wiley and Sons Inc.
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7391344/ https://ncbi.nlm.nih.gov/pubmed/32760523 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/ece3.6448 |
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