wambaugh2019.seem3: ExpoCast SEEM3 Consensus Exposure Model Predictions for...
In httk: High-Throughput Toxicokinetics
wambaugh2019.seem3 R Documentation
ExpoCast SEEM3 Consensus Exposure Model Predictions for Chemical Intake Rates
Description
These data are a subset of the Bayesian inferrences reported by Ring et al.
(2019) for a consensus model of twelve exposue predictors. The predictors
were calibrated based upon their ability to predict intake rates inferred
National Health and Nutrition Examination Survey (NHANES). They reflect the
populaton median intake rate (mg/kg body weight/day), with uncertainty.
Usage
wambaugh2019.seem3
Format
A data frame with 385 rows and 38 variables:
Author(s)
John Wambaugh
Source
Wambaugh et al. (2019)
References
Ring, Caroline L., et al. "Consensus modeling of median chemical
intake for the US population based on predictions of exposure pathways."
Environmental science & technology 53.2 (2018): 719-732.
Wambaugh et al. (2019) "Assessing Toxicokinetic Uncertainty and
Variability in Risk Prioritization", Toxicological Sciences, 172(2), 235-251.
httk documentation built on Sept. 11, 2024, 9:32 p.m.
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| wambaugh2019.seem3 | R Documentation |
ExpoCast SEEM3 Consensus Exposure Model Predictions for Chemical Intake Rates
Description
These data are a subset of the Bayesian inferrences reported by Ring et al. (2019) for a consensus model of twelve exposue predictors. The predictors were calibrated based upon their ability to predict intake rates inferred National Health and Nutrition Examination Survey (NHANES). They reflect the populaton median intake rate (mg/kg body weight/day), with uncertainty.
Usage
wambaugh2019.seem3
Format
A data frame with 385 rows and 38 variables:
Author(s)
John Wambaugh
Source
Wambaugh et al. (2019)
References
Ring, Caroline L., et al. "Consensus modeling of median chemical intake for the US population based on predictions of exposure pathways." Environmental science & technology 53.2 (2018): 719-732.
Wambaugh et al. (2019) "Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization", Toxicological Sciences, 172(2), 235-251.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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