@article{ref1,
title="Bayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes",
journal="Computational statistics and data analysis",
year="2007",
author="Congdon, P.",
volume="51",
number="5",
pages="2586-2601",
abstract="The modelling of spatially varying regression effects for multivariate mortality count outcomes is investigated. Alternative approaches to spatial regression heterogeneity are considered: the multivariate normal conditional autoregressive (MCAR) model is contrasted with a flexible set of priors based on the multiple membership approach. These include spatial factor priors and a non-parametric approach based on the Dirichlet process. A case study considers varying regression effects for a bivariate suicide outcome, namely male and female suicides in 354 English local authorities with social deprivation, social fragmentation and rurality as predictors.  2006 Elsevier B.V. All rights reserved.<p />",
language="",
issn="0167-9473",
doi="10.1016/j.csda.2006.01.004",
url="http://dx.doi.org/10.1016/j.csda.2006.01.004"
}