A unifying modeling framework for highly multivariate disease mapping-Reference-Cited by-同舟云学术

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A unifying modeling framework for highly multivariate disease mapping

Published:2015-01-23 Issue:9 Volume:34 Page:1548-1559
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Botella-Rocamora P.¹,Martinez-Beneito M.A.²³^ORCID,Banerjee S.⁴

Affiliation:

1. Dpto. Ciencias Físicas; Matemáticas y de la Computación. Universidad CEU-Cardenal Herrera. Avda. Seminario; Montcada s/n. 46113 Spain

2. Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana (FISABIO). Av. Catalunya; Valencia 21. 46020 Spain

3. Instituto de Salud Carlos III - Melchor Fernández Almagro; Madrid 3-5, 28029 Spain

4. UCLA Fielding School of Public Health; University of California, Los Angeles; 650 Charles E. Young Drive South 90095-1772 Los Angeles CA

Funder

Ministerio de Economía y Competitividad

Ministerio de Educación, Cultura y Deporte

National Science Foundation

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.6423/fullpdf

Reference25 articles.

1. Bayesian inference for general Gaussian graphical models with application to multivariate lattice data;Dobra;Journal of the American Statistical Association,2011

2. Gaussian Markov Random Fields

3. Generalized common spatial factor model;Wang;Biostatistics,2003

4. Bayesian factor analysis for spatially correlated data, with application to summarizing area-level material deprivation from census data;Hogan;Journal of the American Statistical Association,2004

5. Bayesian latent variable modelling of multivariate spatio-temporal variation in cancer mortality;Tzala;Statistical Methods in Medical Research,2008

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