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Bayesian inference for generalized linear mixed models
Generalized linear mixed models (GLMMs) continue to grow in popularity due to their ability to directly acknowledge multiple levels of dependency and model different data types. For small sample sizes especially, likelihood-based inference can be unreliable with variance components being particularl...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2010
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2883299/ https://ncbi.nlm.nih.gov/pubmed/19966070 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biostatistics/kxp053 |
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