Boundary Cases for Bayesian Benchmark Dose Analysis
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2020/03/01
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Description:In this demonstration, a case study on unanticipated results when applying Bayesian methods to dose-response analyses and benchmark dose estimation is studied. This presentation will discuss advanced considerations in BMD modeling such as model boundary conditions, priors, and flexibility. Specifically, this talk will investigate a dataset where traditional maximum likelihood methods produce unstable estimates and noninformative Bayesian analysis produces results that are not intuitive. The focus will be on the impact of prior selection on results and the importance of conducting sensitivity analysis. Means for integrating toxicological knowledge into priors for Bayesian approaches in BMD analyses will be discussed. [Description provided by NIOSH]
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ISSN:1096-6080
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Volume:174
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Issue:1
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NIOSHTIC Number:nn:20058916
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Citation:Toxicologist 2020 Mar; 174(1):177
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Federal Fiscal Year:2020
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Peer Reviewed:False
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Source Full Name:The Toxicologist. Society of Toxicology 59th Annual Meeting and ToxExpo, March 15-19, 2020, Anaheim, California
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Main Document Checksum:urn:sha-512:af13d2062b3a8cf8359fe5ac97d4c8c54b43f67e2693a2575cf6a503c24e3004c41d86bb6356486a7143ab7f03927d546753e38cc9b299bdcdc6faed21ee0a58
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