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Article: Asymptotically efficient product-limit estimators with censoring indicators missing at random

TitleAsymptotically efficient product-limit estimators with censoring indicators missing at random
Authors
KeywordsMissing at random
Product-limit estimator
Random censorship
Issue Date2008
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 2008, v. 18 n. 2, p. 749-768 How to Cite?
AbstractIn this paper, we develop methods for estimating a survival function with censoring indicators missing at random. The resulting methods lead to the use of imputation and inverse probability weighting. We give several asymptotically efficient PL estimators. All the estimators are proved to be strongly uniformly consistent and weakly convergent to a Gaussian process. Further, it is shown that these estimators are asymptotically efficient. A simulation study was carried out to evaluate the finite sample performances of the proposed estimators and compare the proposed estimators with van der Laan and McKeague's (1998) estimator under missing at random (MAR) and missing completely at random (MCAR) assumptions, respectively.
Persistent Identifierhttp://hdl.handle.net/10722/57164
ISSN
2015 Impact Factor: 0.838
2015 SCImago Journal Rankings: 2.292
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Qen_HK
dc.contributor.authorNg, KWen_HK
dc.date.accessioned2010-04-12T01:27:58Z-
dc.date.available2010-04-12T01:27:58Z-
dc.date.issued2008en_HK
dc.identifier.citationStatistica Sinica, 2008, v. 18 n. 2, p. 749-768en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57164-
dc.description.abstractIn this paper, we develop methods for estimating a survival function with censoring indicators missing at random. The resulting methods lead to the use of imputation and inverse probability weighting. We give several asymptotically efficient PL estimators. All the estimators are proved to be strongly uniformly consistent and weakly convergent to a Gaussian process. Further, it is shown that these estimators are asymptotically efficient. A simulation study was carried out to evaluate the finite sample performances of the proposed estimators and compare the proposed estimators with van der Laan and McKeague's (1998) estimator under missing at random (MAR) and missing completely at random (MCAR) assumptions, respectively.en_HK
dc.languageengen_HK
dc.publisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/en_HK
dc.relation.ispartofStatistica Sinicaen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectMissing at randomen_HK
dc.subjectProduct-limit estimatoren_HK
dc.subjectRandom censorshipen_HK
dc.titleAsymptotically efficient product-limit estimators with censoring indicators missing at randomen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=18&issue=2&spage=749&epage=768&date=2008&atitle=Asymptotically+efficient+product-limit+estimators+with+censoring+indicators+missing+at+randomen_HK
dc.identifier.emailNg, KW: kaing@hkucc.hku.hken_HK
dc.identifier.authorityNg, KW=rp00765en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.scopuseid_2-s2.0-47849115395en_HK
dc.identifier.hkuros146040-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-47849115395&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume18en_HK
dc.identifier.issue2en_HK
dc.identifier.spage749en_HK
dc.identifier.epage768en_HK
dc.publisher.placeTaiwan, Republic of Chinaen_HK
dc.identifier.scopusauthoridWang, Q=35796403100en_HK
dc.identifier.scopusauthoridNg, KW=7403178774en_HK

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