Nonparametric kernel estimation of cure models in survival analysis
| UDC.coleccion | Investigación | |
| UDC.departamento | Matemáticas | |
| UDC.endPage | 22 | |
| UDC.grupoInv | Modelización, Optimización e Inferencia Estatística (MODES) | |
| UDC.institutoCentro | CITIC - Centro de Investigación de Tecnoloxías da Información e da Comunicación | |
| UDC.issue | 3 | |
| UDC.journalTitle | BEIO (Boletín de Estadística e Investigación Operativa) | |
| UDC.startPage | 9 | |
| UDC.volume | 41 | |
| dc.contributor.author | López-Cheda, Ana | |
| dc.contributor.author | Cao, Ricardo | |
| dc.contributor.author | Jácome, M. A. | |
| dc.contributor.author | Keilegom, Ingrid Van | |
| dc.date.accessioned | 2026-02-11T11:35:43Z | |
| dc.date.available | 2026-02-11T11:35:43Z | |
| dc.date.issued | 2025-11-11 | |
| dc.description.abstract | [Abstract]: In lifetime data, there may be long-term survivors, which lead to heavy censoring at the end of the follow-up period. In this context, a standard survival model is not appropriate, and therefore a cure model is needed. In the literature, the covariate effect in mixture cure models was modeled using parametric or semiparametric approaches. Recently, completely nonparametric methods for the cure rate and the latency were proposed in mixture cure models. In this paper, we present this methodology and apply it to a colorectal cancer dataset. | |
| dc.description.sponsorship | The first three authors’ research has been partially supported by the grants PID2020-113578RB-I00 and PID2023-147127OB-I00 ”ERDF/EU”, funded by MCIN/AEI/10.13039/501100011033/. It has also been supported by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2024/14) and by CITIC as a center accredited for excellence within the Galician University System and a member of the CIGUS Network, receives subsidies from the Department of Education, Science, Universities, and Vocational Training of the Xunta de Galicia. Additionally, it is co-financed by the EU through the FEDER Galicia 2021-27 operational program (Ref. ED431G 2023/01). Besides, this work integrated into the framework of PERTE for Cutting-edge Health, has been co-financed by the Spanish Ministry of Science, Innovation and Universities with funds from the European Union NextGenerationEU, from the Recovery, Transformation and Resilience Plan (PRTR-C17.I1) and from the Autonomous Community of Galicia within the framework of the Biotechnology Plan Applied to Health. Ingrid Van Keilegom gratefully acknowledges funding from the FWO and F.R.S. - FNRS (Excellence of Science programme, project ASTeRISK, grant no. G0I3422N), and from the FWO (senior research projects fundamental research, grant no. G047524N). | |
| dc.description.sponsorship | Xunta de Galicia; ED431C-2024/14 | |
| dc.description.sponsorship | Xunta de Galicia; ED431G 2023/01 | |
| dc.description.sponsorship | Bélgica. Fonds Wetenschappelijk Onderzoek; G0I3422N | |
| dc.description.sponsorship | Bélgica. Fonds Wetenschappelijk Onderzoek; G047524N | |
| dc.description.sponsorship | Bélgica. Fonds de la Recherche Scientifique; G047524N | |
| dc.identifier.citation | López-Cheda, A., Cao, R., Jácome, M.A., Van Keilegom, I. (2025). Nonparametric kernel estimation of cure models in survival analysis. Boletín de Estadística e Investigación Operativa. 41(3), 9-22. https://doi.org/10.63552/beio.2025.41.3.02 | |
| dc.identifier.doi | 10.63552/beio.2025.41.3.02 | |
| dc.identifier.issn | 1889-3805 | |
| dc.identifier.uri | https://hdl.handle.net/2183/47363 | |
| dc.language.iso | eng | |
| dc.publisher | SEIO | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/METODOS ESTADISTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORIA Y APLICACIONES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/PID2023-147127OB-I00/ES/INFERENCIA ESTADISTICA UTILIZANDO METODOS FLEXIBLES PARA DATOS COMPLEJOS: TEORIA Y APPLICACIONES | |
| dc.relation.uri | https://doi.org/10.63552/beio.2025.41.3.02 | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | open access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Censored data | |
| dc.subject | Cure models | |
| dc.subject | Kernel estimation | |
| dc.subject | Local maximum likelihood | |
| dc.subject | Survival Analysis | |
| dc.title | Nonparametric kernel estimation of cure models in survival analysis | |
| dc.type | journal article | |
| dc.type.hasVersion | VoR | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 811e9787-a857-4c18-8295-268b4014b4bc | |
| relation.isAuthorOfPublication | 3360aaca-39be-43b4-a458-974e79cdbc6b | |
| relation.isAuthorOfPublication | e629ebcc-3475-4638-b4e7-bf3e786f997c | |
| relation.isAuthorOfPublication.latestForDiscovery | 811e9787-a857-4c18-8295-268b4014b4bc |
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