A Bayesian hierarchical model for risk assessment of methylmercury
This article uses a Bayesian hierarchical model to quantify the adverse health effects associated with in-utero exposure to methylmercury. By allowing for study-to-study as well as outcome-to-outcome variability, the approach provides a useful meta-analytic tool for multi-outcome, multi-study enviro...
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ftunivtsydney:oai:opus.lib.uts.edu.au:10453/26163 2023-05-15T16:10:53+02:00 A Bayesian hierarchical model for risk assessment of methylmercury Coull, BA Mezzetti, M Ryan, LM 2003-09-01 application/pdf http://hdl.handle.net/10453/26163 unknown Journal of Agricultural, Biological, and Environmental Statistics 10.1198/1085711032291 Journal of Agricultural, Biological, and Environmental Statistics, 2003, 8 (3), pp. 253 - 270 1085-7117 http://hdl.handle.net/10453/26163 Statistics & Probability Journal Article 2003 ftunivtsydney 2022-03-13T13:39:22Z This article uses a Bayesian hierarchical model to quantify the adverse health effects associated with in-utero exposure to methylmercury. By allowing for study-to-study as well as outcome-to-outcome variability, the approach provides a useful meta-analytic tool for multi-outcome, multi-study environmental risk assessments. The analysis presented here expands on the findings of a National Academy of Sciences (NAS) committee, charged with advising the United States Environmental Protection Agency (EPA) on an appropriate approach to conducting a risk assessment for methylmercury. The NAS committee, for which the senior author (Ryan) was a committee member, reviewed the findings from several conflicting studies and reported the results from a Bayesian hierarchical model that synthesized information across several studies and for several outcomes. Although the NAS committee did not suggest that the hierarchical model be used as the actual basis for a methylmercury risk assessment, the results from the model were used to justify and support the final recommendation that the risk analysis be based on data from a study conducted in the Faroe Islands, which had found an association between in-utero exposure to methylmercury and impaired neurological development. We consider a variety of statistical issues, but particularly sensitivity to model specification. © 2003 American Statistical Association and the International Biometric Society. Article in Journal/Newspaper Faroe Islands University of Technology Sydney: OPUS - Open Publications of UTS Scholars Faroe Islands |
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University of Technology Sydney: OPUS - Open Publications of UTS Scholars |
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Statistics & Probability |
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Statistics & Probability Coull, BA Mezzetti, M Ryan, LM A Bayesian hierarchical model for risk assessment of methylmercury |
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Statistics & Probability |
description |
This article uses a Bayesian hierarchical model to quantify the adverse health effects associated with in-utero exposure to methylmercury. By allowing for study-to-study as well as outcome-to-outcome variability, the approach provides a useful meta-analytic tool for multi-outcome, multi-study environmental risk assessments. The analysis presented here expands on the findings of a National Academy of Sciences (NAS) committee, charged with advising the United States Environmental Protection Agency (EPA) on an appropriate approach to conducting a risk assessment for methylmercury. The NAS committee, for which the senior author (Ryan) was a committee member, reviewed the findings from several conflicting studies and reported the results from a Bayesian hierarchical model that synthesized information across several studies and for several outcomes. Although the NAS committee did not suggest that the hierarchical model be used as the actual basis for a methylmercury risk assessment, the results from the model were used to justify and support the final recommendation that the risk analysis be based on data from a study conducted in the Faroe Islands, which had found an association between in-utero exposure to methylmercury and impaired neurological development. We consider a variety of statistical issues, but particularly sensitivity to model specification. © 2003 American Statistical Association and the International Biometric Society. |
format |
Article in Journal/Newspaper |
author |
Coull, BA Mezzetti, M Ryan, LM |
author_facet |
Coull, BA Mezzetti, M Ryan, LM |
author_sort |
Coull, BA |
title |
A Bayesian hierarchical model for risk assessment of methylmercury |
title_short |
A Bayesian hierarchical model for risk assessment of methylmercury |
title_full |
A Bayesian hierarchical model for risk assessment of methylmercury |
title_fullStr |
A Bayesian hierarchical model for risk assessment of methylmercury |
title_full_unstemmed |
A Bayesian hierarchical model for risk assessment of methylmercury |
title_sort |
bayesian hierarchical model for risk assessment of methylmercury |
publishDate |
2003 |
url |
http://hdl.handle.net/10453/26163 |
geographic |
Faroe Islands |
geographic_facet |
Faroe Islands |
genre |
Faroe Islands |
genre_facet |
Faroe Islands |
op_relation |
Journal of Agricultural, Biological, and Environmental Statistics 10.1198/1085711032291 Journal of Agricultural, Biological, and Environmental Statistics, 2003, 8 (3), pp. 253 - 270 1085-7117 http://hdl.handle.net/10453/26163 |
_version_ |
1765996015908814848 |