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Robustness of the BYM model in absence of spatial variation in the residuals
BACKGROUND: In the context of ecological studies, the Bayesian hierarchical Poisson model is of prime interest when studying the association between environmental exposure and rare diseases. However, adding spatially structured extra-variability in the model fitted to the data when such extra-variab...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241594/ https://www.ncbi.nlm.nih.gov/pubmed/17883857 http://dx.doi.org/10.1186/1476-072X-6-39 |
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author | Latouche, Aurélien Guihenneuc-Jouyaux, Chantal Girard, Claire Hémon, Denis |
author_facet | Latouche, Aurélien Guihenneuc-Jouyaux, Chantal Girard, Claire Hémon, Denis |
author_sort | Latouche, Aurélien |
collection | PubMed |
description | BACKGROUND: In the context of ecological studies, the Bayesian hierarchical Poisson model is of prime interest when studying the association between environmental exposure and rare diseases. However, adding spatially structured extra-variability in the model fitted to the data when such extra-variability does not exist conditionally on the covariates included in the model (over-fitting) may bias the estimation of the ecological association between covariates and relative risks toward the null. In order to investigate that possibility, a simulation study of the impact of introducing unnecessary residual spatial structure in the estimation model was conducted. RESULTS: In the case where no underlying extra-variability from the Poisson process exists, the simulation results show that models accounting for structured and unstructured residuals do not underestimate the ecological association, unless covariates have a very strong autocorrelation structure, i.e., 0.98 at 100 km on a territory of diameter 1000 km." |
format | Text |
id | pubmed-2241594 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-22415942008-02-13 Robustness of the BYM model in absence of spatial variation in the residuals Latouche, Aurélien Guihenneuc-Jouyaux, Chantal Girard, Claire Hémon, Denis Int J Health Geogr Research BACKGROUND: In the context of ecological studies, the Bayesian hierarchical Poisson model is of prime interest when studying the association between environmental exposure and rare diseases. However, adding spatially structured extra-variability in the model fitted to the data when such extra-variability does not exist conditionally on the covariates included in the model (over-fitting) may bias the estimation of the ecological association between covariates and relative risks toward the null. In order to investigate that possibility, a simulation study of the impact of introducing unnecessary residual spatial structure in the estimation model was conducted. RESULTS: In the case where no underlying extra-variability from the Poisson process exists, the simulation results show that models accounting for structured and unstructured residuals do not underestimate the ecological association, unless covariates have a very strong autocorrelation structure, i.e., 0.98 at 100 km on a territory of diameter 1000 km." BioMed Central 2007-09-20 /pmc/articles/PMC2241594/ /pubmed/17883857 http://dx.doi.org/10.1186/1476-072X-6-39 Text en Copyright © 2007 Latouche et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Latouche, Aurélien Guihenneuc-Jouyaux, Chantal Girard, Claire Hémon, Denis Robustness of the BYM model in absence of spatial variation in the residuals |
title | Robustness of the BYM model in absence of spatial variation in the residuals |
title_full | Robustness of the BYM model in absence of spatial variation in the residuals |
title_fullStr | Robustness of the BYM model in absence of spatial variation in the residuals |
title_full_unstemmed | Robustness of the BYM model in absence of spatial variation in the residuals |
title_short | Robustness of the BYM model in absence of spatial variation in the residuals |
title_sort | robustness of the bym model in absence of spatial variation in the residuals |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2241594/ https://www.ncbi.nlm.nih.gov/pubmed/17883857 http://dx.doi.org/10.1186/1476-072X-6-39 |
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