Publication Type

Journal Article

Version

publishedVersion

Publication Date

7-2017

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

Discipline

Economics

Research Areas

Econometrics

Publication

Journal of the Royal Statistical Society: Series C: Applied Statistics

First Page

1

Last Page

26

ISSN

0035-9254

Identifier

10.1111/rssc.12230

Publisher

Wiley

Additional URL

https://doi.org/10.1111/rssc.12230

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Economics Commons

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