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A Bayesian space–time model for clustering areal units based on their disease trends
Population-level disease risk across a set of non-overlapping areal units varies in space and time, and a large research literature has developed methodology for identifying clusters of areal units exhibiting elevated risks. However, almost no research has extended the clustering paradigm to identif...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797054/ https://www.ncbi.nlm.nih.gov/pubmed/29917057 http://dx.doi.org/10.1093/biostatistics/kxy024 |