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Article: Dose-response curve estimation: A semiparametric mixture approach

TitleDose-response curve estimation: A semiparametric mixture approach
Authors
KeywordsBootstrap
Dose-response curve
Effective dose
Nonparametric method
Parametric model
Weighted average
Issue Date2011
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM
Citation
Biometrics, 2011, v. 67 n. 4, p. 1543-1554 How to Cite?
AbstractIn the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples. © 2011, The International Biometric Society.
Persistent Identifierhttp://hdl.handle.net/10722/139714
ISSN
2015 Impact Factor: 1.36
2015 SCImago Journal Rankings: 1.906
ISI Accession Number ID
Funding AgencyGrant Number
National Cancer Institute (USA)R01CA154591-01A1
Research Grants Council of Hong Kong
Funding Information:

We would like to thank the two referees, the associate editor, and the editor (Professor G. Verbeke) for very insightful and constructive comments that led to a substantial improvement of our article. The research of Ying Yuan was partially supported by the National Cancer Institute (USA) Grant R01CA154591-01A1, and the research of Guosheng Yin was partially supported by a grant from the Research Grants Council of Hong Kong.

References

 

DC FieldValueLanguage
dc.contributor.authorYuan, Yen_HK
dc.contributor.authorYin, Gen_HK
dc.date.accessioned2011-09-23T05:54:45Z-
dc.date.available2011-09-23T05:54:45Z-
dc.date.issued2011en_HK
dc.identifier.citationBiometrics, 2011, v. 67 n. 4, p. 1543-1554en_HK
dc.identifier.issn0006-341Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/139714-
dc.description.abstractIn the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples. © 2011, The International Biometric Society.en_HK
dc.languageengen_US
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOMen_HK
dc.relation.ispartofBiometricsen_HK
dc.rightsThe definitive version is available at www.blackwell-synergy.com-
dc.subjectBootstrapen_HK
dc.subjectDose-response curveen_HK
dc.subjectEffective doseen_HK
dc.subjectNonparametric methoden_HK
dc.subjectParametric modelen_HK
dc.subjectWeighted averageen_HK
dc.subject.meshBiometry - methodsen_HK
dc.subject.meshDose-Response Relationship, Drugen_HK
dc.subject.meshDrug Therapy, Computer-Assisted - methodsen_HK
dc.subject.meshModels, Biologicalen_HK
dc.subject.meshModels, Statisticalen_HK
dc.titleDose-response curve estimation: A semiparametric mixture approachen_HK
dc.typeArticleen_HK
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1541-0420.2011.01620.xen_HK
dc.identifier.pmid21627631-
dc.identifier.scopuseid_2-s2.0-83655201490en_HK
dc.identifier.hkuros195634en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-83655201490&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume67en_HK
dc.identifier.issue4en_HK
dc.identifier.spage1543en_HK
dc.identifier.epage1554en_HK
dc.identifier.isiWOS:000298095900038-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridYuan, Y=7402709174en_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK

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