A unifying modeling framework for highly multivariate disease mapping

Multivariate disease mapping refers to the joint mapping of multiple diseases from regionally aggregated data and continues to be the subject of considerable attention for biostatisticians and spatial epidemiologists. The key issue is to map multiple diseases accounting for any correlations among th...

Full description

Saved in:
Bibliographic Details
Published in:Statistics in medicine 2015-04, Vol.34 (9), p.1548-1559
Main Authors: Botella-Rocamora, P., Martinez-Beneito, M.A., Banerjee, S.
Format: Article
Language:English
Subjects:
Biostatistics
Cause of Death
Computer Simulation
Correlation analysis
disease mapping
Epidemiologic Methods
Epidemiology
Geographic Information Systems
hierarchical Bayesian models
Humans
Male
Mathematical models
Mathematical problems
Mortality
Multivariate Analysis
Spain - epidemiology
Spatial Analysis
spatial modeling
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Multivariate disease mapping refers to the joint mapping of multiple diseases from regionally aggregated data and continues to be the subject of considerable attention for biostatisticians and spatial epidemiologists. The key issue is to map multiple diseases accounting for any correlations among themselves. Recently, Martinez‐Beneito (2013) provided a unifying framework for multivariate disease mapping. While attractive in that it colligates a variety of existing statistical models for mapping multiple diseases, this and other existing approaches are computationally burdensome and preclude the multivariate analysis of moderate to large numbers of diseases. Here, we propose an alternative reformulation that accrues substantial computational benefits enabling the joint mapping of tens of diseases. Furthermore, the approach subsumes almost all existing classes of multivariate disease mapping models and offers substantial insight into the properties of statistical disease mapping models. Copyright © 2015 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.6423