Multiple imputation for competing risks survival data via pseudo-observations
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Han, Seungbong | - |
dc.contributor.author | Andrei, Adin-Cristian | - |
dc.contributor.author | Tsui, Kam-Wah | - |
dc.date.available | 2020-02-27T10:41:17Z | - |
dc.date.created | 2020-02-07 | - |
dc.date.issued | 2018-07 | - |
dc.identifier.issn | 2287-7843 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/3607 | - |
dc.description.abstract | Competing risks are commonly encountered in biomedical research. Regression models for competing risks data can be developed based on data routinely collected in hospitals or general practices. However, these data sets usually contain the covariate missing values. To overcome this problem, multiple imputation is often used to fit regression models under a MAR assumption. Here, we introduce a multivariate imputation in a chained equations algorithm to deal with competing risks survival data. Using pseudo-observations, we make use of the available outcome information by accommodating the competing risk structure. Lastly, we illustrate the practical advantages of our approach using simulations and two data examples from a coronary artery disease data and hepatocellular carcinoma data. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | KOREAN STATISTICAL SOC | - |
dc.relation.isPartOf | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | - |
dc.subject | CUMULATIVE INCIDENCE FUNCTION | - |
dc.subject | CHAINED EQUATIONS | - |
dc.subject | MISSING CAUSES | - |
dc.subject | RANDOM FOREST | - |
dc.subject | VALUES | - |
dc.subject | MODEL | - |
dc.subject | MICE | - |
dc.title | Multiple imputation for competing risks survival data via pseudo-observations | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000441620900005 | - |
dc.identifier.doi | 10.29220/CSAM.2018.25.4.385 | - |
dc.identifier.bibliographicCitation | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.25, no.4, pp.385 - 396 | - |
dc.identifier.kciid | ART002371070 | - |
dc.identifier.scopusid | 2-s2.0-85054015581 | - |
dc.citation.endPage | 396 | - |
dc.citation.startPage | 385 | - |
dc.citation.title | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | - |
dc.citation.volume | 25 | - |
dc.citation.number | 4 | - |
dc.contributor.affiliatedAuthor | Han, Seungbong | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | competing risks | - |
dc.subject.keywordAuthor | missing data | - |
dc.subject.keywordAuthor | multiple imputation | - |
dc.subject.keywordAuthor | pseudo-observations | - |
dc.subject.keywordAuthor | random forest | - |
dc.subject.keywordPlus | CUMULATIVE INCIDENCE FUNCTION | - |
dc.subject.keywordPlus | CHAINED EQUATIONS | - |
dc.subject.keywordPlus | MISSING CAUSES | - |
dc.subject.keywordPlus | RANDOM FOREST | - |
dc.subject.keywordPlus | VALUES | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | MICE | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
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