Difference between revisions of "Monte Carlo Risk Assessment, July 2007"
(New page: RIVM and Wacheningen University have developed a monte carlo model for estimating risk from dietary intake.This page briefly summarizes what the model is about.) |
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RIVM and Wacheningen University have developed a monte carlo model for estimating risk from dietary intake.This page briefly summarizes what the model is about. | RIVM and Wacheningen University have developed a monte carlo model for estimating risk from dietary intake.This page briefly summarizes what the model is about. | ||
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| + | In a Monte Carlo dietary risk assessment the risk of exposure to pesticides or other chemicals from the diet is quantified by combining database information on food consumption with database information from monitoring programs for residues of chemicals in food. | ||
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| + | MCRA is intended for users who want to analyze their own consumption and chemical concentration data. MCRA provides the following options<br># acute (short-term) risk assessment<br># chronic (long-term) risk assessment<br># empirical or parametric modelling of residue levels<br># modelling of processing effects, unit variability and nondetects levels<br># bootstrapping to assess the uncertainty of percentiles<br># comparison with deterministic point estimates (IESTI) | ||
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| + | For questions please contact:<br>MailJacob van Klaveren (RIKILT/KAP, residue and food consumption data sets, applications), or<br>MailHilko van der Voet (Biometris, statistical methods, program development)<br> | ||
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| + | = Summary = | ||
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Revision as of 09:57, 2 April 2008
RIVM and Wacheningen University have developed a monte carlo model for estimating risk from dietary intake.This page briefly summarizes what the model is about.
In a Monte Carlo dietary risk assessment the risk of exposure to pesticides or other chemicals from the diet is quantified by combining database information on food consumption with database information from monitoring programs for residues of chemicals in food.
MCRA is intended for users who want to analyze their own consumption and chemical concentration data. MCRA provides the following options
# acute (short-term) risk assessment
# chronic (long-term) risk assessment
# empirical or parametric modelling of residue levels
# modelling of processing effects, unit variability and nondetects levels
# bootstrapping to assess the uncertainty of percentiles
# comparison with deterministic point estimates (IESTI)
For questions please contact:
MailJacob van Klaveren (RIKILT/KAP, residue and food consumption data sets, applications), or
MailHilko van der Voet (Biometris, statistical methods, program development)
Summary
