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A Flexible Bayesian Approach to Monotone Missing Data in Longitudinal Studies with Nonignorable Missingness with Application to an Acute Schizophrenia Clinical Trial
We develop a Bayesian nonparametric model for a longitudinal response in the presence of nonignorable missing data. Our general approach is to first specify a working model that flexibly models the missingness and full outcome processes jointly. We specify a Dirichlet process mixture of missing at r...
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| Veröffentlicht in: | J Am Stat Assoc |
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| Hauptverfasser: | , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2015
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4517693/ https://ncbi.nlm.nih.gov/pubmed/26236060 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2014.969424 |
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