Robustness of the BYM model in absence of spatial variation in the residuals View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2007-12

AUTHORS

Aurélien Latouche, Chantal Guihenneuc-Jouyaux, Claire Girard, Denis Hémon

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." More... »

PAGES

39

References to SciGraph publications

  • 1991-03. Bayesian image restoration, with two applications in spatial statistics in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/1476-072x-6-39

    DOI

    http://dx.doi.org/10.1186/1476-072x-6-39

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1025440025

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/17883857


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