In epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease aetiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. We propose using a Bayesian analysis based on the conditional autoregressive (
Bayesian spatial models with repeated measurements: with application to the herbaceous data analysis
โ Scribed by Xiaoqian Sun; Zhuoqiong He; Jing Zhang; John Kabrick
- Publisher
- Springer
- Year
- 2009
- Tongue
- English
- Weight
- 490 KB
- Volume
- 18
- Category
- Article
- ISSN
- 1613-981X
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