Risk assessment of dietary exposure to pesticides using a Bayesian method

M.J. Paulo, H. van der Voet, M.J.W. Jansen, C.J.F. ter Braak, J.D. van Klaveren

Research output: Contribution to journalArticleAcademicpeer-review

41 Citations (Scopus)


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
Original languageEnglish
Pages (from-to)759-766
JournalPest Management Science
Issue number8
Publication statusPublished - 2005


  • food chemicals
  • validation
  • regression
  • models

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