Journal article
A multivariate CAR model for mismatched lattices
Spatial and spatio-temporal epidemiology, Vol.11, pp.79-88
10/2014
DOI: 10.1016/j.sste.2014.08.001
PMCID: PMC7185497
PMID: 25457598
Abstract
In this paper, we develop a multivariate Gaussian conditional autoregressive model for use on mismatched lattices. Most current multivariate CAR models are designed for each multivariate outcome to utilize the same lattice structure. In many applications, a change of basis will allow different lattices to be utilized, but this is not always the case, because a change of basis is not always desirable or even possible. Our multivariate CAR model allows each outcome to have a different neighborhood structure which can utilize different lattices for each structure. The model is applied in two real data analysis. The first is a Bayesian learning example in mapping the 2006 Iowa Mumps epidemic, which demonstrates the importance of utilizing multiple channels of infection flow in mapping infectious diseases. The second is a multivariate analysis of poverty levels and educational attainment in the American Community Survey.
Details
- Title: Subtitle
- A multivariate CAR model for mismatched lattices
- Creators
- Aaron T Porter - Colorado School of Mines, Department of Applied Mathematics and Statistics, United States. Electronic address: aporter@mines.eduJacob J Oleson - University of Iowa, Department of Biostatistics, United States. Electronic address: jacob-oleson@uiowa.edu
- Resource Type
- Journal article
- Publication Details
- Spatial and spatio-temporal epidemiology, Vol.11, pp.79-88
- Publisher
- Netherlands
- DOI
- 10.1016/j.sste.2014.08.001
- PMID
- 25457598
- PMCID
- PMC7185497
- ISSN
- 1877-5845
- eISSN
- 1877-5853
- Language
- English
- Date published
- 10/2014
- Academic Unit
- Biostatistics
- Record Identifier
- 9983997306902771
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