Bayesian Ecological Study
A Bayesian ecological study combines the group-level observational design of classical ecological epidemiology with Bayesian hierarchical modelling. Rather than treating disease rates as fixed quantities, it places prior distributions over latent spatial or temporal effects — commonly using the Besag-York-Mollié (BYM) convolution prior — and updates beliefs from aggregate data to produce posterior maps of disease risk, smoothed rate estimates, and credible intervals for ecological associations between exposures and outcomes.
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- Lawson, A. B. (2013). Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (2nd ed.). CRC Press. · ISBN 978-1466504813
- Besag, J., York, J., & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1–20. · DOI 10.1007/BF00116466
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