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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...
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| Published in: | Int J Environ Res Public Health |
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| Main Authors: | , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
MDPI
2015
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4586634/ https://ncbi.nlm.nih.gov/pubmed/26343704 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijerph120910648 |
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