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Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes
BACKGROUND: Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of healt...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2014
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4287494/ https://www.ncbi.nlm.nih.gov/pubmed/25410053 http://dx.doi.org/10.1186/1476-072X-13-47 |