Combining data from multiple sources, with applications to environmental risk assessment

Ryan, L

Combining data from multiple sources, with applications to environmental risk assessment

Ryan, L

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Publication Type:: Journal Article
Citation:: Statistics in Medicine, 2008, 27 (5), pp. 698 - 710
Issue Date:: 2008-02-28

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Field	Value	Language
dc.contributor.author	Ryan, L https://orcid.org/0000-0001-5957-2490	en_US
dc.date.issued	2008-02-28	en_US
dc.identifier.citation	Statistics in Medicine, 2008, 27 (5), pp. 698 - 710	en_US
dc.identifier.issn	0277-6715	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26050
dc.description.abstract	The classical statistical paradigm emphasizes the development and application of methods to account for sampling variability. Many modern day applications, however, require consideration of other sources of uncertainty that are not so easy to quantify. This paper presents a case study involving an assessment of the impact of in-utero methylmercury exposure on the Intelligence Quotient (IQ) of young children. We illustrate how familiar techniques such as hierarchical modeling, Bayesian methods and sensitivity analysis can be used to aid decision making in settings that involve substantial uncertainty. Copyright © 2007 John Wiley & Sons, Ltd.	en_US
dc.relation.ispartof	Statistics in Medicine	en_US
dc.relation.isbasedon	10.1002/sim.3053	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Methylmercury Compounds	en_US
dc.subject.mesh	Hazardous Substances	en_US
dc.subject.mesh	Data Interpretation, Statistical	en_US
dc.subject.mesh	Risk Assessment	en_US
dc.subject.mesh	Uncertainty	en_US
dc.subject.mesh	Intelligence	en_US
dc.subject.mesh	Decision Making	en_US
dc.subject.mesh	Environmental Exposure	en_US
dc.title	Combining data from multiple sources, with applications to environmental risk assessment	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	27	en_US
utslib.for	010402 Biostatistics	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1117 Public Health and Health Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

The classical statistical paradigm emphasizes the development and application of methods to account for sampling variability. Many modern day applications, however, require consideration of other sources of uncertainty that are not so easy to quantify. This paper presents a case study involving an assessment of the impact of in-utero methylmercury exposure on the Intelligence Quotient (IQ) of young children. We illustrate how familiar techniques such as hierarchical modeling, Bayesian methods and sensitivity analysis can be used to aid decision making in settings that involve substantial uncertainty. Copyright © 2007 John Wiley & Sons, Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/26050