Semiparametric accelerated failure time cure rate mixture models with competing risks
DC Field | Value | Language |
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dc.contributor.author | Choi, Sangbum | - |
dc.contributor.author | Zhu, Liang | - |
dc.contributor.author | Huang, Xuelin | - |
dc.date.accessioned | 2021-09-02T16:11:13Z | - |
dc.date.available | 2021-09-02T16:11:13Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2018-01-15 | - |
dc.identifier.issn | 0277-6715 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/77982 | - |
dc.description.abstract | Modern medical treatments have substantially improved survival rates for many chronic diseases and have generated considerable interest in developing cure fraction models for survival data with a non-ignorable cured proportion. Statistical analysis of such data may be further complicated by competing risks that involve multiple types of endpoints. Regression analysis of competing risks is typically undertaken via a proportional hazards model adapted on cause-specific hazard or subdistribution hazard. In this article, we propose an alternative approach that treats competing events as distinct outcomes in a mixture. We consider semiparametric accelerated failure time models for the cause-conditional survival function that are combined through a multinomial logistic model within the cure-mixture modeling framework. The cure-mixture approach to competing risks provides a means to determine the overall effect of a treatment and insights into how this treatment modifies the components of the mixture in the presence of a cure fraction. The regression and nonparametric parameters are estimated by a nonparametric kernel-based maximum likelihood estimation method. Variance estimation is achieved through resampling methods for the kernel-smoothed likelihood function. Simulation studies show that the procedures work well in practical settings. Application to a sarcoma study demonstrates the use of the proposed method for competing risk data with a cure fraction. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.subject | EFFICIENT ESTIMATION | - |
dc.subject | SURVIVAL-DATA | - |
dc.subject | TRANSFORMATION MODELS | - |
dc.subject | REGRESSION-ANALYSIS | - |
dc.subject | CENSORED-DATA | - |
dc.subject | INFERENCE | - |
dc.subject | FRACTION | - |
dc.title | Semiparametric accelerated failure time cure rate mixture models with competing risks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Sangbum | - |
dc.identifier.doi | 10.1002/sim.7508 | - |
dc.identifier.scopusid | 2-s2.0-85037672067 | - |
dc.identifier.wosid | 000417483900004 | - |
dc.identifier.bibliographicCitation | STATISTICS IN MEDICINE, v.37, no.1, pp.48 - 59 | - |
dc.relation.isPartOf | STATISTICS IN MEDICINE | - |
dc.citation.title | STATISTICS IN MEDICINE | - |
dc.citation.volume | 37 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 48 | - |
dc.citation.endPage | 59 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalResearchArea | Medical Informatics | - |
dc.relation.journalResearchArea | Research & Experimental Medicine | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Medical Informatics | - |
dc.relation.journalWebOfScienceCategory | Medicine, Research & Experimental | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | EFFICIENT ESTIMATION | - |
dc.subject.keywordPlus | SURVIVAL-DATA | - |
dc.subject.keywordPlus | TRANSFORMATION MODELS | - |
dc.subject.keywordPlus | REGRESSION-ANALYSIS | - |
dc.subject.keywordPlus | CENSORED-DATA | - |
dc.subject.keywordPlus | INFERENCE | - |
dc.subject.keywordPlus | FRACTION | - |
dc.subject.keywordAuthor | competing risks | - |
dc.subject.keywordAuthor | cure fraction | - |
dc.subject.keywordAuthor | kernel smoothing | - |
dc.subject.keywordAuthor | mixture model | - |
dc.subject.keywordAuthor | nonparametric likelihood | - |
dc.subject.keywordAuthor | subdistribution | - |
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