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A fast Monte Carlo EM algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with AGC

In this article we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Mon...

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Autors principals: Kang, Le, Carter, Randy, Darcy, Kathleen, Kauderer, James, Liao, Shu-Yuan
Format: Artigo
Idioma:Inglês
Publicat: 2013
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC3806648/
https://ncbi.nlm.nih.gov/pubmed/24163493
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/02664763.2013.825704
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