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Analysis of spatial data with a nested correlation structure

Author

Listed:
  • Oyelola A. Adegboye
  • Denis H. Y. Leung
  • You‐Gan Wang

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.

Suggested Citation

  • Oyelola A. Adegboye & Denis H. Y. Leung & You‐Gan Wang, 2018. "Analysis of spatial data with a nested correlation structure," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 329-354, February.
    • Handle: RePEc:bla:jorssc:v:67:y:2018:i:2:p:329-354
    DOI: 10.1111/rssc.12230
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    Cited by:

    1. Theophilus I. Emeto & Oyelola A. Adegboye & Reza A. Rumi & Mahboob-Ul I. Khan & Majeed Adegboye & Wasif A. Khan & Mahmudur Rahman & Peter K. Streatfield & Kazi M. Rahman, 2020. "Disparities in Risks of Malaria Associated with Climatic Variability among Women, Children and Elderly in the Chittagong Hill Tracts of Bangladesh," IJERPH, MDPI, vol. 17(24), pages 1-15, December.
    2. Chung‐Wei Shen & Chun‐Shu Chen, 2024. "Estimation and selection for spatial zero‐inflated count models," Environmetrics, John Wiley & Sons, Ltd., vol. 35(4), June.

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