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Activity Number: 156
Type: Topic Contributed
Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #311163 View Presentation
Title: Bayesian Model Averaging in Benchmark Dose Estimation
Author(s): Susan Simmons*+ and Cuixian Chen and Xiaosong Li and Yishi Wang and Walt Piegorsch and Qijun Fang and Troy Kling and Otis Evans
Companies: University of North Carolina at Wilmington and University of North Carolina at Wilmington and UNCW and UNCW and University of Arizona and University of Arizona and UNCW and UNCW
Keywords: Bayesian ; Benchmark analysis ; model averaging
Abstract:

Estimation of benchmark dose is an important topic in environmental risk assessment. However, when using parametric methods, a risk model must be specified. Identifying the incorrect risk model can lead to erroneous estimation and decisions regarding the benchmark dose. Instead of chosing one risk model, we developed a Bayesian model averaged estimator that utilizes all potential risk models and averages across them, allowing models with best fits to have the highest weights. We demonstrate the usefulness of this methodology on a simulated data set.


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