Spatial modelling of cluster object and non-specific random effects, with application in spatial epidemiology

The spatial modelling of small area health data has, for some time, included spatial autocorrelation as a random effect. This effect is nonspecific and global and does not address the location of clusters of disease (a specific task). This paper addresses the need for specific and non-specific random effects within spatial epidemiology. In addition, individual frailty is also considered important and computational algorithms based on a range of MCMC methods are described. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.