Pseudolikelihood Modeling of Multivariate Outcomes in Developmental Toxicology

Geys, H; Molenberghs, G; Ryan, LM

Pseudolikelihood Modeling of Multivariate Outcomes in Developmental Toxicology

Geys, H Molenberghs, G Ryan, LM

Permalink

Publication Type:: Journal Article
Citation:: Journal of the American Statistical Association, 1999, 94 (447), pp. 734 - 745
Issue Date:: 1999-09-01

Closed Access

	Filename	Description	Size
	2011008584OK.pdf		1.76 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Geys, H	en_US
dc.contributor.author	Molenberghs, G	en_US
dc.contributor.author	Ryan, LM https://orcid.org/0000-0001-5957-2490	en_US
dc.date.issued	1999-09-01	en_US
dc.identifier.citation	Journal of the American Statistical Association, 1999, 94 (447), pp. 734 - 745	en_US
dc.identifier.issn	0162-1459	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26180
dc.description.abstract	The primary goal of this article is to determine benchmark doses based on the ethylene glycol study, which comprises data from a developmental toxicity study in mice. Because the data involve a vector of malformation indicators, a flexible model for multivariate clustered data is required. An exponential family model is considered and pseudolikelihood-based inferential tools are proposed, hence avoiding excessive computational requirements. © 1999 Taylor & Francis Group, LLC.	en_US
dc.relation.ispartof	Journal of the American Statistical Association	en_US
dc.relation.isbasedon	10.1080/01621459.1999.10474176	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Pseudolikelihood Modeling of Multivariate Outcomes in Developmental Toxicology	en_US
dc.type	Journal Article
utslib.citation.volume	447	en_US
utslib.citation.volume	94	en_US
utslib.for	010402 Biostatistics	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1403 Econometrics	en_US
utslib.for	1603 Demography	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	447	en_US
pubs.publication-status	Published	en_US
pubs.volume	94	en_US

Abstract:

The primary goal of this article is to determine benchmark doses based on the ethylene glycol study, which comprises data from a developmental toxicity study in mice. Because the data involve a vector of malformation indicators, a flexible model for multivariate clustered data is required. An exponential family model is considered and pseudolikelihood-based inferential tools are proposed, hence avoiding excessive computational requirements. © 1999 Taylor & Francis Group, LLC.

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

http://hdl.handle.net/10453/26180