Citation

Congdon P. Comput. Stat. Data Anal. 2007; 51(5): 2586-2601.

Copyright

(Copyright © 2007, Elsevier Publishing)

DOI

10.1016/j.csda.2006.01.004

PMID

unavailable

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.