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Analysis of spatial data with a nested correlation structure
Adegboye, Oyelola Leung, Denis Wang, You-Gan
Adegboye, Oyelola
Leung, Denis
Wang, You-Gan
Abstract
Spatial statistical analyses are often used to study the link between environmental factors and the incidence of diseases. In modelling spatial data, the existence of spatial correlation between observations must be considered. However, in many situations, the exact form of the spatial correlation is unknown. This paper studies environmental factors that might influence the incidence of malaria in Afghanistan. We assume that spatial correlation may be induced by multiple latent sources. Our method is based on a generalized estimating equation of the marginal mean of disease incidence, as a function of the geographical factors and the spatial correlation. Instead of using one set of generalized estimating equations, we embed a series of generalized estimating equations, each reflecting a particular source of spatial correlation, into a larger system of estimating equations. To estimate the spatial correlation parameters, we set up a supplementary set of estimating equations based on the correlation structures that are induced from the various sources. Simultaneous estimation of the mean and correlation parameters is performed by alternating between the two systems of equations.
Keywords
Generalized estimating equations, Generalized method of moments, Malaria, Poisson model, Spatial correlation
Date
2018
Type
Journal article
Journal
Book
Volume
67
Issue
2
Page Range
329-354
Article Number
ACU Department
Institute for Learning Sciences and Teacher Education (ILSTE)
Faculty of Education and Arts
Faculty of Education and Arts
Relation URI
Event URL
Open Access Status
License
All rights reserved
File Access
Controlled
Notes
© 2017 Royal Statistical Society