Premium
A Bayesian multivariate analysis of children's exposure to pesticides
Author(s) -
Cressie N.,
Morara M.,
Buxton B.,
McMillan N.,
Strauss W.,
Wilson N.
Publication year - 2013
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.2220
Subject(s) - multivariate statistics , bayesian probability , chlorpyrifos , statistics , multivariate analysis , pesticide , computer science , econometrics , mathematics , biology , ecology
In this article, we present a multivariate Bayesian analysis of the relationships, in preschool children, between environmental pathways of exposure to a nonpersistent pesticide, chlorpyrifos, and its corresponding biomarker in urine, trichloropyridinol. The analysis uses the 3 years of data from the Pesticide Exposures of Preschool Children Over Time study. Hierarchical Bayesian analysis of pathways of exposure has gained popularity in recent years, where missing and censored data are modeled, and measurement and regression errors are accounted for in a single hierarchical statistical model. Here we consider multivariate pathways, where chlorpyrifos and its metabolite trichloropyridinol are modeled jointly in the environmental media. In this article, we analyze each of the three years of the study, focusing on the within‐year multivariate nature of the Pesticide Exposures of Preschool Children Over Time data set. We present the results in a way that allows for an easy comparison of the fitted parameters over time. Copyright © 2013 John Wiley & Sons, Ltd.