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Flexible Random Intercept Models for Binary Outcomes Using Mixtures of Normals
Random intercept models for binary data are useful tools for addressing between-subject heterogeneity. Unlike linear models, the non-linearity of link functions used for binary data force a distinction between marginal and conditional interpretations. This distinction is blurred in probit models wit...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2007
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2031853/ https://ncbi.nlm.nih.gov/pubmed/18628822 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csda.2006.09.031 |
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