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Article: Semiparametric transformation models for survival data with a cure fraction
Title | Semiparametric transformation models for survival data with a cure fraction |
---|---|
Authors | |
Keywords | Cure model Linear transformation models Proportional hazards model Proportional odds model Semiparametric efficiency |
Issue Date | 2006 |
Publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main |
Citation | Journal Of The American Statistical Association, 2006, v. 101 n. 474, p. 670-684 How to Cite? |
Abstract | We propose a class of transformation models for survival data with a cure fraction. The class of transformation models is motivated by biological considerations and includes both the proportional ha/ards and the proportional odds cure models as two special cases. An efficient recursive algorithm is proposed to calculate the maximum likelihood estimators (MLEs). Furthermore, the MLEs for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic variances attain the semiparametric efficiency bound. Simulation studies arc conducted to examine the finite-sample properties of the proposed estimators. The method is illustrated on data from a clinical trial involving the treatment of melanoma. © 2006 American Statistical Association. |
Persistent Identifier | http://hdl.handle.net/10722/146574 |
ISSN | 2023 Impact Factor: 3.0 2023 SCImago Journal Rankings: 3.922 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zeng, D | en_HK |
dc.contributor.author | Yin, G | en_HK |
dc.contributor.author | Ibrahim, JG | en_HK |
dc.date.accessioned | 2012-05-02T08:37:07Z | - |
dc.date.available | 2012-05-02T08:37:07Z | - |
dc.date.issued | 2006 | en_HK |
dc.identifier.citation | Journal Of The American Statistical Association, 2006, v. 101 n. 474, p. 670-684 | en_HK |
dc.identifier.issn | 0162-1459 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/146574 | - |
dc.description.abstract | We propose a class of transformation models for survival data with a cure fraction. The class of transformation models is motivated by biological considerations and includes both the proportional ha/ards and the proportional odds cure models as two special cases. An efficient recursive algorithm is proposed to calculate the maximum likelihood estimators (MLEs). Furthermore, the MLEs for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic variances attain the semiparametric efficiency bound. Simulation studies arc conducted to examine the finite-sample properties of the proposed estimators. The method is illustrated on data from a clinical trial involving the treatment of melanoma. © 2006 American Statistical Association. | en_HK |
dc.language | eng | en_US |
dc.publisher | American Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main | en_HK |
dc.relation.ispartof | Journal of the American Statistical Association | en_HK |
dc.subject | Cure model | en_HK |
dc.subject | Linear transformation models | en_HK |
dc.subject | Proportional hazards model | en_HK |
dc.subject | Proportional odds model | en_HK |
dc.subject | Semiparametric efficiency | en_HK |
dc.title | Semiparametric transformation models for survival data with a cure fraction | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Yin, G: gyin@hku.hk | en_HK |
dc.identifier.authority | Yin, G=rp00831 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1198/016214505000001122 | en_HK |
dc.identifier.scopus | eid_2-s2.0-33645578210 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-33645578210&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 101 | en_HK |
dc.identifier.issue | 474 | en_HK |
dc.identifier.spage | 670 | en_HK |
dc.identifier.epage | 684 | en_HK |
dc.identifier.isi | WOS:000238033200022 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Zeng, D=8725807700 | en_HK |
dc.identifier.scopusauthorid | Yin, G=8725807500 | en_HK |
dc.identifier.scopusauthorid | Ibrahim, JG=7005341361 | en_HK |
dc.identifier.citeulike | 644122 | - |
dc.identifier.issnl | 0162-1459 | - |