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An assessment of estimation methods for generalized linear mixed models with binary outcomes
Two main classes of methodology have been developed for addressing the analytical intractability of generalized linear mixed models (GLMMs): likelihood-based methods and Bayesian methods. Likelihood-based methods such as the penalized quasi-likelihood approach have been shown to produce biased estim...
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| Huvudupphovsmän: | , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2013
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3866838/ https://ncbi.nlm.nih.gov/pubmed/23839712 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.5866 |
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