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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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Main Authors: | , , , |
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Formato: | Artigo |
Idioma: | Inglês |
Publicado em: |
2011
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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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