Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2577
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dc.contributor.authorGEYS, Helena-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorWilliams, Paige-
dc.date.accessioned2007-11-15T11:01:43Z-
dc.date.available2007-11-15T11:01:43Z-
dc.date.issued2002-
dc.identifier.citationJOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 7(2). p. 176-190-
dc.identifier.issn1085-7117-
dc.identifier.urihttp://hdl.handle.net/1942/2577-
dc.description.abstractThe standard approach for analysis of teratology studies is to use a population-averaged model with primary interest on evaluating dose-response effects. For example, generalized estimating equations (GEEs) have become popular for analysis of both developmental toxicity and reproductive studies (Ryan 1992). Such an approach is typically appropriate since the covariate of interest-exposure level-is constant for each litter of animals. Recently, however, there has been growing interest in evaluating effects of covariates that can vary between individuals within a cluster. This article explores several opportunities generated by teratology studies with individual-level covariates both in terms of modeling approaches and in decomposition of litter effects into genetic and environmental components.-
dc.description.sponsorshipThe authorsthank Stuart Lipsitz for providinghis SAS macro forrst-order generalized estimating equations, Dr. Gary Kimmel for access to the heatshock data, and Russell Wolnger for several helpful suggestions.This work was supported by the NATO CollaborativeResearch Grant 950648,FWO-Vlaanderen, Belgium, and by NIH grant ES07981-01.This research was carried out in part while the rst and second authors were visiting the Department of Biostatistics at the Harvard School of Public Health. The research of the rst author was additionally supported by the Institute for the Promotion of Innovation by Science and Technology (IWT) in Flanders, Belgium.-
dc.language.isoen-
dc.publisherAMER STATISTICAL ASSOC & INTERNATIONAL BIOMETRIC SOC-
dc.rights(C) 2002 American Statistical Association and the International Biometric Society-
dc.subject.othercluster specic; correlated binary data; developmental toxicology; generalized estimating equations; marginal model; population averaged-
dc.subject.othercluster specific; correlated binary data; developmental toxicology; generalized estimating equations; marginal model; population averaged-
dc.titleAnalysis of toxicology data with covariates specific to each observation-
dc.typeJournal Contribution-
dc.identifier.epage190-
dc.identifier.issue2-
dc.identifier.spage176-
dc.identifier.volume7-
local.format.pages15-
local.bibliographicCitation.jcatA1-
dc.description.notesLimburgs Univ Ctr, B-3590 Diepenbeek, Belgium. Harvard Univ, Sch Publ Hlth, Boston, MA 02115 USA.-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1198/10857110260141229-
dc.identifier.isi000176010000004-
item.fulltextWith Fulltext-
item.contributorGEYS, Helena-
item.contributorMOLENBERGHS, Geert-
item.contributorWilliams, Paige-
item.fullcitationGEYS, Helena; MOLENBERGHS, Geert & Williams, Paige (2002) Analysis of toxicology data with covariates specific to each observation. In: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 7(2). p. 176-190.-
item.accessRightsRestricted Access-
item.validationecoom 2003-
crisitem.journal.issn1085-7117-
crisitem.journal.eissn1537-2693-
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