Multiple imputation analysis for propensity score matching with missing causes of failure: An application to hepatocellular carcinoma data
DC Field | Value | Language |
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dc.contributor.author | Han, Seungbong | - |
dc.contributor.author | Tsui, Kam-Wah | - |
dc.contributor.author | Zhang, Hui | - |
dc.contributor.author | Kim, Gi-Ae | - |
dc.contributor.author | Lim, Young-Suk | - |
dc.contributor.author | Andrei, Adin-Cristian | - |
dc.date.accessioned | 2022-02-18T19:41:14Z | - |
dc.date.available | 2022-02-18T19:41:14Z | - |
dc.date.created | 2022-02-07 | - |
dc.date.issued | 2021-10 | - |
dc.identifier.issn | 0962-2802 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/136258 | - |
dc.description.abstract | Propensity score matching is widely used to determine the effects of treatments in observational studies. Competing risk survival data are common to medical research. However, there is a paucity of propensity score matching studies related to competing risk survival data with missing causes of failure. In this study, we provide guidelines for estimating the treatment effect on the cumulative incidence function when using propensity score matching on competing risk survival data with missing causes of failure. We examined the performances of different methods for imputing the data with missing causes. We then evaluated the gain from the missing cause imputation in an extensive simulation study and applied the proposed data imputation method to the data from a study on the risk of hepatocellular carcinoma in patients with chronic hepatitis B and chronic hepatitis C. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SAGE PUBLICATIONS LTD | - |
dc.subject | COMPETING RISKS DATA | - |
dc.subject | CUMULATIVE INCIDENCE | - |
dc.subject | SURVIVAL-DATA | - |
dc.subject | INFERENCE | - |
dc.subject | MODEL | - |
dc.subject | PERFORMANCE | - |
dc.subject | REGRESSION | - |
dc.title | Multiple imputation analysis for propensity score matching with missing causes of failure: An application to hepatocellular carcinoma data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Han, Seungbong | - |
dc.identifier.doi | 10.1177/09622802211037075 | - |
dc.identifier.scopusid | 2-s2.0-85114084042 | - |
dc.identifier.wosid | 000692573700001 | - |
dc.identifier.bibliographicCitation | STATISTICAL METHODS IN MEDICAL RESEARCH, v.30, no.10, pp.2313 - 2328 | - |
dc.relation.isPartOf | STATISTICAL METHODS IN MEDICAL RESEARCH | - |
dc.citation.title | STATISTICAL METHODS IN MEDICAL RESEARCH | - |
dc.citation.volume | 30 | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 2313 | - |
dc.citation.endPage | 2328 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Health Care Sciences & Services | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Medical Informatics | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Medical Informatics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | COMPETING RISKS DATA | - |
dc.subject.keywordPlus | CUMULATIVE INCIDENCE | - |
dc.subject.keywordPlus | INFERENCE | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | REGRESSION | - |
dc.subject.keywordPlus | SURVIVAL-DATA | - |
dc.subject.keywordAuthor | Competing risks | - |
dc.subject.keywordAuthor | hepatocellular carcinoma | - |
dc.subject.keywordAuthor | matching | - |
dc.subject.keywordAuthor | missing causes | - |
dc.subject.keywordAuthor | propensity score | - |
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