A0197
Title: Bayesian modelling for spatially misaligned health areal data
Authors: Silvia Liverani - Queen Mary University of London (United Kingdom) [presenting]
Abstract: The objective of disease mapping is to model data aggregated at the areal level. In some contexts, however (e.g. residential histories, general practitioner catchment areas), when data arising from a variety of sources, not necessarily at the same spatial scale, it is possible to specify spatial random effects or covariate effects at the areal level, by using a multiple membership principle. The purpose is to investigate the theoretical underpinnings of this application of the multiple membership principle to the CAR prior, in particular with regard to parameterization, properness and identifiability, and the results of an application of the multiple membership model to diabetes prevalence data in South London are presented, together with strategic implications for public health considerations.
