A0680
Title: Modelling spatially correlated binary data
Authors: Youjun Huang - Sichuan University (China) [presenting]
Gabrielle Kelly - University College Dublin (Ireland)
Jianxin Pan - The University of Manchester (United Kingdom)
Abstract: Generalized estimating equations lead to consistent estimators of the mean parameters for spatially correlated binary data, but the estimation of covariance matrix is also of interest in spatial data analysis. A specific parametric form is proposed to model the correlation matrix for spatially correlated binary data. An iterative approach based on generalized estimating equations is developed to estimate the mean and correlation parameters simultaneously. Asymptotic normality for the estimators of the mean and correlation parameters is provided. Simulation studies are conducted through considering various model parameters such as different working correlation matrices, correlation parameters and dimensions of the mean parameters. The proposed approach is used to analyze the spatial bovine tuberculosis infection data in Ireland, aiming to quantify the influence of some important factors on the infection for both badgers and cattle, as well as the correlation between their setts and herds.
