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A Hidden Markov Model approach to analyze longitudinal ternary outcomes when some observed states are possibly misclassified

Understanding the dynamic disease process is vital in early detection, diagnosis, and measuring progression. Continuous-time Markov chain (CTMC) methods have been used to estimate state change intensities but challenges arise when stages are potentially misclassified. We present an analytical likeli...

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Detalhes bibliográficos
Publicado no:Stat Med
Main Authors: Benoit, Julia S., Chan, Wenyaw, Luo, Sheng, Yeh, Hung-Wen, Doody, Rachelle
Formato: Artigo
Idioma:Inglês
Publicado em: 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4821697/
https://ncbi.nlm.nih.gov/pubmed/26782946
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.6861
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