Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/28519
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dc.contributor.authorLi, E-
dc.contributor.authorYu, K-
dc.contributor.authorTang, ML-
dc.contributor.authorTian, M-
dc.date.accessioned2024-03-12T16:24:01Z-
dc.date.available2024-03-12T16:24:01Z-
dc.date.issued2024-
dc.identifierORCiD: Man-Lai Tang https://orcid.org/0000-0003-3934-2676-
dc.identifierORCiD: Keming Yu https://orcid.org/0000-0001-6341-8402-
dc.identifier.citationLi, E. et al. (2024) 'Optimal subsampling proportional subdistribution hazards regression with rare events in big data', Statistics and its Interface, 0 (accepted, in press), pp. 1 - 17.en_US
dc.identifier.issn1938-7989-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/28519-
dc.descriptionThe data set is provided by Surveillance Research Program, National Cancer Institute SEER*Stat software (seer.cancer.gov/seerstat) version 8.3.9.1.en_US
dc.description.abstract...en_US
dc.description.sponsorshipNational Natural Science Funds of China (Grant No. 12101015); Scientific Research Foundation of North China University of Technology (No. 110051360002); Fundamental Research Funds for Beijing Universities, NCUT (No.110052971921/007); National Natural Science Foundation of China (No.11861042); China Statistical Research Project (No. 2020LZ25).en_US
dc.language.isoen_USen_US
dc.publisherInternational Pressen_US
dc.rightsCopyright © 2024 International Press. A copy of the published Work may be posted to an institutional repository or archive, whose content is accessible solely to users within the institution, at an institution with whom the Author was affiliated at the time of the Work’s publication by the Publisher (see: https://www.intlpress.com/site/pub/files/journal_author_ctp_form/author_consent_to_publish_form_cms.pdf).-
dc.rights.urihttps://www.intlpress.com/site/pub/files/journal_author_ctp_form/author_consent_to_publish_form_cms.pdf-
dc.subjectbig dataen_US
dc.subjectcompeting risks dataen_US
dc.subjectoptimal subsamplingen_US
dc.titleOptimal subsampling proportional subdistribution hazards regression with rare events in big dataen_US
dc.typeArticleen_US
dc.relation.isPartOfStatistics and its Interface-
pubs.publication-statusAccepted-
dc.rights.holderInternational Press-
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