Publication: Statistical methods for bivariate spatial analysis in marked points. Examples in spatial epidemiology
Issued Date
2011-12-01
Resource Type
ISSN
18775853
18775845
18775845
Other identifier(s)
2-s2.0-80053448550
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Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Spatial and Spatio-temporal Epidemiology. Vol.2, No.4 (2011), 227-234
Suggested Citation
Marc Souris, Laurence Bichaud Statistical methods for bivariate spatial analysis in marked points. Examples in spatial epidemiology. Spatial and Spatio-temporal Epidemiology. Vol.2, No.4 (2011), 227-234. doi:10.1016/j.sste.2011.06.001 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/11912
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Title
Statistical methods for bivariate spatial analysis in marked points. Examples in spatial epidemiology
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Abstract
This article presents methods to analyze global spatial relationships between two variables in two different sets of fixed points. Analysis of spatial relationships between two phenomena is of great interest in health geography and epidemiology, especially to highlight competing interest between phenomena or evidence of a common environmental factor. Our general approach extends the Moran and Pearson indices to the bivariate case in two different sets of points. The case where the variables are Boolean is treated separately through methods using nearest neighbors distances. All tests use Monte-Carlo simulations to estimate their probability distributions, with options to distinguish spatial and no spatial correlation in the special case of identical sets analysis. Implementation in a Geographic Information System (SavGIS) and real examples are used to illustrate these spatial indices and methods in epidemiology. © 2011 Elsevier Ltd.