title: Risk assessment of dietary exposure to pesticides using a Bayesian method.
abstract: Risk assessment of pesticides can be a statistically difficult problem because pesticides occur only occasionally, but they may occur on multiple components in the diet. A Bayesian statistical model is presented which incorporates multivariate modelling of food consumption and modelling of pesticide measurements which are for a large part below a measurement threshold. It is shown that Bayesian modelling is feasible for a limited number of food components, and that in a data-rich situation the model compares well with an empirical Monte Carlo modelling.
authors.affiliation: Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands.
authors.forename: M João
authors.initials: MJ
authors.lastname: Paulo
authors.forename: Hilko
authors.initials: H
authors.lastname: van der Voet
authors.forename: Michiel J W
authors.initials: MJ
authors.lastname: Jansen
authors.forename: Cajo J F
authors.initials: CJ
authors.lastname: ter Braak
authors.forename: Jacob D
authors.initials: JD
authors.lastname: van Klaveren
mesh_terms: D001499:Bayes Theorem; D005506:Food Contamination; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D010573:Pesticide Residues / Q000633:toxicity*; D018570:Risk Assessment
chemical_list: D010573:Pesticide Residues