Sciweavers

Share
CSDA
2007

Bayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes

10 years 11 months ago
Bayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes
This paper considers modelling spatially varying regression effects for multivariate mortality count outcomes. 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 nonparametric 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. Key Words: Spatially varying regression effects. Multiple Members Model. Conditional autoregressive priors. Multivariate Response. Suicide
P. Congdon
Added 25 Dec 2010
Updated 25 Dec 2010
Type Journal
Year 2007
Where CSDA
Authors P. Congdon
Comments (0)
books