Abstract:
:An important objective in biomedical and environmental risk assessment is estimation of minimum exposure levels that induce a pre-specified adverse response in a target population. The exposure points in such settings are typically referred to as benchmark doses (BMDs). Parametric Bayesian estimation for finding BMDs has grown in popularity, and a large variety of candidate dose-response models is available for applying these methods. Each model can possess potentially different parametric interpretation(s), however. We present reparameterized dose-response models that allow for explicit use of prior information on the target parameter of interest, the BMD. We also enhance our Bayesian estimation technique for BMD analysis by applying Bayesian model averaging to produce point estimates and (lower) credible bounds, overcoming associated questions of model adequacy when multimodel uncertainty is present. An example from carcinogenicity testing illustrates the calculations.
journal_name
Biometricsjournal_title
Biometricsauthors
Fang Q,Piegorsch WW,Simmons SJ,Li X,Chen C,Wang Ydoi
10.1111/biom.12340subject
Has Abstractpub_date
2015-12-01 00:00:00pages
1168-75issue
4eissn
0006-341Xissn
1541-0420journal_volume
71pub_type
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