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A Two-Latent-Class Model for Smoking Cessation Data with Informative Dropouts

Non ignorable missing data is a common problem in longitudinal studies. Latent class models are attractive for simplifying the modeling of missing data when the data are subject to either a monotone or intermittent missing data pattern. In our study, we propose a new two-latent-class model for categ...

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Detalhes bibliográficos
Main Authors: QIN, LI, WEISSFELD, LISA A., SHEN, CHANGYU, LEVINE, MICHELE D.
Formato: Artigo
Idioma:Inglês
Publicado em: 2009
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC2879593/
https://ncbi.nlm.nih.gov/pubmed/20523912
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/03610920802585849
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