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An exploration of fixed and random effects selection for longitudinal binary outcomes in the presence of nonignorable dropout
We explore a Bayesian approach to selection of variables that represent fixed and random effects in modeling of longitudinal binary outcomes with missing data caused by dropouts. We show via analytic results for a simple example that nonignorable missing data lead to biased parameter estimates. This...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2012
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3855104/ https://ncbi.nlm.nih.gov/pubmed/23124889 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/bimj.201100107 |
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