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A Bayesian Approach to Account for Misclassification and Overdispersion in Count Data
Count data are subject to considerable sources of what is often referred to as non-sampling error. Errors such as misclassification, measurement error and unmeasured confounding can lead to substantially biased estimators. It is strongly recommended that epidemiologists not only acknowledge these so...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2015
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586634/ https://www.ncbi.nlm.nih.gov/pubmed/26343704 http://dx.doi.org/10.3390/ijerph120910648 |