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BAYESIAN MODELING LONGITUDINAL DYADIC DATA WITH NONIGNORABLE DROPOUT, WITH APPLICATION TO A BREAST CANCER STUDY
Dyadic data are common in the social and behavioral sciences, in which members of dyads are correlated due to the interdependence structure within dyads. The analysis of longitudinal dyadic data becomes complex when nonignorable dropouts occur. We propose a fully Bayesian selection-model-based appro...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2012
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3693094/ https://ncbi.nlm.nih.gov/pubmed/23814631 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/11-AOAS515 |
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