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Bayesian Latent-class Mixed-effect Hybrid Models for Dyadic Longitudinal Data with Non-ignorable Dropouts
The analysis of longitudinal dyadic data is challenging due to the complicated correlations within and between dyads, as well as possibly non-ignorable dropouts. Based on a mixed-effects hybrid model, we propose an approach to analyze longitudinal dyadic data with non-ignorable dropouts. We factoriz...
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| Главные авторы: | , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2013
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3970927/ https://ncbi.nlm.nih.gov/pubmed/24328715 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12100 |
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