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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-08-01
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| Series: | International Journal of Environmental Research and Public Health |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1660-4601/12/9/10648 |