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Growth Modeling with Non-Ignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial

This paper uses a general latent variable framework to study a series of models for non-ignorable missingness due to dropout. Non-ignorable missing data modeling acknowledges that missingness may depend on not only covariates and observed outcomes at previous time points as with the standard missing...

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Detalhes bibliográficos
Main Authors: Muthén, Bengt, Asparouhov, Tihomir, Hunter, Aimee, Leuchter, Andrew
Formato: Artigo
Idioma:Inglês
Publicado em: 2011
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3060937/
https://ncbi.nlm.nih.gov/pubmed/21381817
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1037/a0022634
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