Linked Life Data

17883857

Source:http://linkedlifedata.com/resource/pubmed/id/17883857

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-2-13
pubmed:abstractText
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."
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1476-072X
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
39
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Robustness of the BYM model in absence of spatial variation in the residuals.
pubmed:affiliation
Inserm, U754, Villejuif, F-94807, France. aurelien.latouche@paris7.jussieu.fr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't