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Article: Partial linear models for longitudinal data based on quadratic inference functions

TitlePartial linear models for longitudinal data based on quadratic inference functions
Authors
KeywordsB-spline
Estimating equations
Longitudinal data
Partial linear models
Quadratic inference functions
Issue Date2008
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOS
Citation
Scandinavian Journal Of Statistics, 2008, v. 35 n. 1, p. 104-118 How to Cite?
AbstractIn this paper, we consider improved estimating equations for semiparametric partial linear models (PLM) for longitudinal data, or clustered data in general. We approximate the non-parametric function in the PLM by a regression spline, and utilize quadratic inference functions (QIF) in the estimating equations to achieve a more efficient estimation of the parametric part in the model, even when the correlation structure is misspecified. Moreover, we construct a test which is an analogue to the likelihood ratio inference function for inferring the parametric component in the model. The proposed methods perform well in simulation studies and real data analysis conducted in this paper. © Board of the Foundation of the Scandinavian Journal of Statistics 2007.
Persistent Identifierhttp://hdl.handle.net/10722/82789
ISSN
2015 Impact Factor: 0.908
2015 SCImago Journal Rankings: 1.362
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorBai, Yen_HK
dc.contributor.authorZhu, Zen_HK
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2010-09-06T08:33:26Z-
dc.date.available2010-09-06T08:33:26Z-
dc.date.issued2008en_HK
dc.identifier.citationScandinavian Journal Of Statistics, 2008, v. 35 n. 1, p. 104-118en_HK
dc.identifier.issn0303-6898en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82789-
dc.description.abstractIn this paper, we consider improved estimating equations for semiparametric partial linear models (PLM) for longitudinal data, or clustered data in general. We approximate the non-parametric function in the PLM by a regression spline, and utilize quadratic inference functions (QIF) in the estimating equations to achieve a more efficient estimation of the parametric part in the model, even when the correlation structure is misspecified. Moreover, we construct a test which is an analogue to the likelihood ratio inference function for inferring the parametric component in the model. The proposed methods perform well in simulation studies and real data analysis conducted in this paper. © Board of the Foundation of the Scandinavian Journal of Statistics 2007.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOSen_HK
dc.relation.ispartofScandinavian Journal of Statisticsen_HK
dc.rightsScandinavian Journal of Statistics. Copyright © Blackwell Publishing Ltd.en_HK
dc.subjectB-splineen_HK
dc.subjectEstimating equationsen_HK
dc.subjectLongitudinal dataen_HK
dc.subjectPartial linear modelsen_HK
dc.subjectQuadratic inference functionsen_HK
dc.titlePartial linear models for longitudinal data based on quadratic inference functionsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0303-6898&volume=35&spage=104&epage=118&date=2008&atitle=Partial+linear+models+for+longitudinal+data+based+on+quadratic+inference+functionsen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1467-9469.2007.00578.xen_HK
dc.identifier.scopuseid_2-s2.0-38849158518en_HK
dc.identifier.hkuros149248en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-38849158518&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue1en_HK
dc.identifier.spage104en_HK
dc.identifier.epage118en_HK
dc.identifier.isiWOS:000253948000006-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridBai, Y=36084084600en_HK
dc.identifier.scopusauthoridZhu, Z=23487505000en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.citeulike2350977-

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