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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/11912
Title: Statistical methods for bivariate spatial analysis in marked points. Examples in spatial epidemiology
Authors: Marc Souris
Laurence Bichaud
Mahidol University
Asian Institute of Technology Thailand
Universite de la Mediterranee Aix-Marseille II
Keywords: Environmental Science;Medicine;Social Sciences
Issue Date: 1-Dec-2011
Citation: Spatial and Spatio-temporal Epidemiology. Vol.2, No.4 (2011), 227-234
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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80053448550&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/11912
ISSN: 18775853
18775845
Appears in Collections:Scopus 2011-2015

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