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Article
A Bayesian multivariate analysis of children’s exposure to pesticides
Centre for Statistical & Survey Methodology Working Paper Series
  • Noel Cressie, University of Wollongong
  • M Morara, Battelle Memorial Institute Columbus
  • B Buxton, Battelle Memorial Institute Columbus
  • N McMillan, Battelle Memorial Institute Columbus
  • W Strauss, Battelle Memorial Institute Columbus
  • N Wilson, Battelle Memorial Institute Durham
Publication Date
1-1-2013
Abstract

In this article, we present a multivariate Bayesian analysis of the relationships, in preschool children, between environmental pathways of exposure to a non-persistent pesticide, chlorpyrifos (CPF), and its corresponding biomarker in urine, trichloropyridinol (TCP). The analysis uses the three years of data from the Pesticide Exposures of Preschool Children Over Time (PEPCOT) 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 CPF and its metabolite TCP 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 PEPCOT data set. We present the results in a way that allows for an easy comparison of the fitted parameters over time.

Citation Information
Noel Cressie, M Morara, B Buxton, N McMillan, et al.. "A Bayesian multivariate analysis of children’s exposure to pesticides" (2013)
Available at: http://works.bepress.com/noel_cressie/302/