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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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Publicado no: | Stat Med |
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Main Authors: | , , , , |
Formato: | Artigo |
Idioma: | Inglês |
Publicado em: |
2016
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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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