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Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping
BACKGROUND: Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2011
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3204220/ https://ncbi.nlm.nih.gov/pubmed/21978359 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1476-072X-10-54 |
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