1. Misspecification of within-area exposure distribution in ecological Poisson models
- Author
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Léa Fortunato, Dominique Laurier, Chantal Guihenneuc-Jouyaux, Denis Hémon, Margot Tirmarche, Epidémiologie environnementale des cancers, Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS ), Institut de Radioprotection et de Sûreté Nucléaire ( IRSN ), and Guihenneuc-Jouyaux, Chantal
- Subjects
Statistics and Probability ,Gaussian ,chemistry.chemical_element ,Radon ,Poisson distribution ,01 natural sciences ,010104 statistics & probability ,03 medical and health sciences ,symbols.namesake ,0302 clinical medicine ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,Statistics ,Gamma distribution ,Econometrics ,[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST] ,0101 mathematics ,Robustness (economics) ,[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST] ,ComputingMilieux_MISCELLANEOUS ,General Environmental Science ,[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH] ,Ecology ,Confounding ,Variance (accounting) ,[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH] ,[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH] ,chemistry ,030220 oncology & carcinogenesis ,symbols ,Environmental science ,Statistics, Probability and Uncertainty ,Scale (map) - Abstract
Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France.
- Published
- 2007
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