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Computational Techniques for Spatial Logistic Regression with Large Datasets
In epidemiological research, outcomes are frequently non-normal, sample sizes may be large, and effect sizes are often small. To relate health outcomes to geographic risk factors, fast and powerful methods for fitting spatial models, particularly for non-normal data, are required. I focus on binary...
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2007
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2350194/ https://ncbi.nlm.nih.gov/pubmed/18443645 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csda.2006.11.008 |
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