Weighting estimation in the cause-specific Cox regression with partially missing causes of failure
DC Field | Value | Language |
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dc.contributor.author | Lee, Jooyoung | - |
dc.contributor.author | Ogino, Shuji | - |
dc.contributor.author | Wang, Molin | - |
dc.date.accessioned | 2024-05-16T05:30:24Z | - |
dc.date.available | 2024-05-16T05:30:24Z | - |
dc.date.issued | 2024-06 | - |
dc.identifier.issn | 0277-6715 | - |
dc.identifier.issn | 1097-0258 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73678 | - |
dc.description.abstract | Complex diseases are often analyzed using disease subtypes classified by multiple biomarkers to study pathogenic heterogeneity. In such molecular pathological epidemiology research, we consider a weighted Cox proportional hazard model to evaluate the effect of exposures on various disease subtypes under competing-risk settings in the presence of partially or completely missing biomarkers. The asymptotic properties of the inverse and augmented inverse probability-weighted estimating equation methods are studied with a general pattern of missing data. Simulation studies have been conducted to demonstrate the double robustness of the estimators. For illustration, we applied this method to examine the association between pack-years of smoking before the age of 30 and the incidence of colorectal cancer subtypes defined by a combination of four tumor molecular biomarkers (statuses of microsatellite instability, CpG island methylator phenotype, BRAF mutation, and KRAS mutation) in the Nurses' Health Study cohort. | - |
dc.format.extent | 17 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | WILEY | - |
dc.title | Weighting estimation in the cause-specific Cox regression with partially missing causes of failure | - |
dc.type | Article | - |
dc.identifier.doi | 10.1002/sim.10084 | - |
dc.identifier.bibliographicCitation | STATISTICS IN MEDICINE, v.43, no.13, pp 2575 - 2591 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 001207577300001 | - |
dc.identifier.scopusid | 2-s2.0-85191316437 | - |
dc.citation.endPage | 2591 | - |
dc.citation.number | 13 | - |
dc.citation.startPage | 2575 | - |
dc.citation.title | STATISTICS IN MEDICINE | - |
dc.citation.volume | 43 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | augmented inverse probability weighting | - |
dc.subject.keywordAuthor | competing risks | - |
dc.subject.keywordAuthor | etiologic heterogeneity | - |
dc.subject.keywordAuthor | partially missing causes | - |
dc.subject.keywordPlus | COMPETING RISKS MODEL | - |
dc.subject.keywordPlus | MOLECULAR PATHOLOGICAL EPIDEMIOLOGY | - |
dc.subject.keywordPlus | MULTIPLE IMPUTATION METHODS | - |
dc.subject.keywordPlus | BREAST-CANCER RISK | - |
dc.subject.keywordPlus | COLORECTAL-CANCER | - |
dc.subject.keywordPlus | SUBTYPES | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | COEFFICIENTS | - |
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.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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