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Article: Estimation in a semiparametric model for longitudinal data with unspecified dependence structure

TitleEstimation in a semiparametric model for longitudinal data with unspecified dependence structure
Authors
He, XZhu, ZYFung, WK
KeywordsB-spline
M-estimator
Mixed model
Rate of convergence
Regression median
Repeated measures
Issue Date2002
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 2002, v. 89 n. 3, p. 579-590 How to Cite?
DOI: http://dx.doi.org/10.1093/biomet/89.3.579
AbstractThis paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large-sample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases are the analysis of the conditional mean and median functions for longitudinal data. © 2002 Biometrika Trust.
Persistent Identifierhttp://hdl.handle.net/10722/82883
ISSN
0006-3444
2023 Impact Factor: 2.4
2023 SCImago Journal Rankings: 3.358
ISI Accession Number ID
WOS:000178151800007
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorHe, Xen_HK
dc.contributor.authorZhu, ZYen_HK
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2010-09-06T08:34:29Z-
dc.date.available2010-09-06T08:34:29Z-
dc.date.issued2002en_HK
dc.identifier.citationBiometrika, 2002, v. 89 n. 3, p. 579-590en_HK
dc.identifier.issn0006-3444en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82883-
dc.description.abstractThis paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M-estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large-sample inferences about the regression parameters without any specification of the error distribution and the covariance structure. Included as special cases are the analysis of the conditional mean and median functions for longitudinal data. © 2002 Biometrika Trust.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_HK
dc.relation.ispartofBiometrikaen_HK
dc.rightsBiometrika. Copyright © Oxford University Press.en_HK
dc.subjectB-splineen_HK
dc.subjectM-estimatoren_HK
dc.subjectMixed modelen_HK
dc.subjectRate of convergenceen_HK
dc.subjectRegression medianen_HK
dc.subjectRepeated measuresen_HK
dc.titleEstimation in a semiparametric model for longitudinal data with unspecified dependence structureen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-3444&volume=89&issue=3&spage=579&epage=590&date=2002&atitle=Estimation+in+a+semiparametric+model+for+longitudinal+data+with+unspecified+dependence+structureen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/biomet/89.3.579en_HK
dc.identifier.scopuseid_2-s2.0-0344128624en_HK
dc.identifier.hkuros80144en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0344128624&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume89en_HK
dc.identifier.issue3en_HK
dc.identifier.spage579en_HK
dc.identifier.epage590en_HK
dc.identifier.isiWOS:000178151800007-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridHe, X=7404407842en_HK
dc.identifier.scopusauthoridZhu, ZY=23487505000en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.citeulike7558185-
dc.identifier.issnl0006-3444-

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