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Robustness of the BYM model in absence of spatial variation in the residuals.


ABSTRACT: 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."

SUBMITTER: Latouche A 

PROVIDER: S-EPMC2241594 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Robustness of the BYM model in absence of spatial variation in the residuals.

Latouche Aurélien A   Guihenneuc-Jouyaux Chantal C   Girard Claire C   Hémon Denis D  

International journal of health geographics 20070920


<h4>Background</h4>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  ...[more]

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