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Doubly Penalized Buckley–James Method for Survival Data with High-Dimensional Covariates
dc.contributor.authorWang, Sijianen_US
dc.contributor.authorNan, Binen_US
dc.contributor.authorZhu, Jien_US
dc.contributor.authorBeer, David G.en_US
dc.date.accessioned2010-04-01T14:59:11Z
dc.date.available2010-04-01T14:59:11Z
dc.date.issued2008-03en_US
dc.identifier.citationWang, Sijian; Nan, Bin; Zhu, Ji; Beer, David G. (2008). "Doubly Penalized Buckley–James Method for Survival Data with High-Dimensional Covariates." Biometrics 64(1): 132-140. <http://hdl.handle.net/2027.42/65445>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/65445
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=17680828&dopt=citationen_US
dc.description.abstractRecent interest in cancer research focuses on predicting patients' survival by investigating gene expression profiles based on microarray analysis. We propose a doubly penalized Buckley–James method for the semiparametric accelerated failure time model to relate high-dimensional genomic data to censored survival outcomes, which uses the elastic-net penalty that is a mixture of L 1 - and L 2 -norm penalties. Similar to the elastic-net method for a linear regression model with uncensored data, the proposed method performs automatic gene selection and parameter estimation, where highly correlated genes are able to be selected (or removed) together. The two-dimensional tuning parameter is determined by generalized crossvalidation. The proposed method is evaluated by simulations and applied to the Michigan squamous cell lung carcinoma study.en_US
dc.format.extent187182 bytes
dc.format.extent3110 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Incen_US
dc.rights2007 International Biometric Societyen_US
dc.subject.otherAccelerated Failure Time Modelen_US
dc.subject.otherBuckley–James Methoden_US
dc.subject.otherCensored Survival Dataen_US
dc.subject.otherElastic Neten_US
dc.subject.otherHigh-dimensional Covariateen_US
dc.subject.otherLung Canceren_US
dc.subject.otherMicroarray Analysisen_US
dc.subject.otherVariable Selectionen_US
dc.titleDoubly Penalized Buckley–James Method for Survival Data with High-Dimensional Covariatesen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.en_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.en_US
dc.contributor.affiliationumDepartments of Surgery and Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.en_US
dc.identifier.pmid17680828en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/65445/1/j.1541-0420.2007.00877.x.pdf
dc.identifier.doi10.1111/j.1541-0420.2007.00877.xen_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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