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보건조사연구에서 다변량결측치가 내포된 자료를 효율적으로 분석하기 위한 통계학적 방법

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dc.contributor.author김동기-
dc.contributor.author김한중-
dc.contributor.author박은철-
dc.contributor.author박형욱-
dc.contributor.author손명세-
dc.contributor.author송기준-
dc.date.accessioned2020-07-02T18:12:01Z-
dc.date.available2020-07-02T18:12:01Z-
dc.date.issued1998-
dc.identifier.issn0254-5985-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/177211-
dc.description.abstractMissing observations are common in medical research and health survey research. Several statistical methods to handle the missing data problem have been proposed. The EM algorithm (Expectation-Maximization algorithm) is one of the ways of efficiently handling the missing data problem based on sufficient statistics. In this paper, we developed statistical models and methods for survey data with multivariate missing observations. Especially, we adopted the EM algorithm to handle the multivariate missing observations. We assume that the multivariate observations follow a multivariate normal distribution, where the mean vector and the covariance matrix are primarily of interest. We applied the proposed statistical method to analyze data from a health survey. The data set we used came from a physician survey on Resource-Based Relative Value Scale(RBRVS). In addition to the EM algorithm, we applied the complete case analysis, which uses only completely observed cases, and the available case analysis, which utilizes all available information. The residual and normal probability plots were evaluated to access the assumption of normality. We found that the residual sum of squares from the EM algorithm was smaller than those of the complete-case and the available-case analyses.-
dc.description.statementOfResponsibilityopen-
dc.languageKorean-
dc.publisher대한예방의학회-
dc.relation.isPartOfKorean Journal of Preventive Medicine (예방의학회지)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.title보건조사연구에서 다변량결측치가 내포된 자료를 효율적으로 분석하기 위한 통계학적 방법-
dc.title.alternativeStatistical Methods for Multivariate Missing Data in Health Survey Research-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biomedical Systems Informatics (의생명시스템정보학교실)-
dc.contributor.googleauthor김동기-
dc.contributor.googleauthor박은철-
dc.contributor.googleauthor손명세-
dc.contributor.googleauthor김한중-
dc.contributor.googleauthor박형욱-
dc.contributor.googleauthor안재형-
dc.contributor.googleauthor임종건-
dc.contributor.googleauthor송기준-
dc.contributor.localIdA00399-
dc.contributor.localIdA01102-
dc.contributor.localIdA01618-
dc.contributor.localIdA01757-
dc.contributor.localIdA01966-
dc.contributor.localIdA02016-
dc.relation.journalcodeJ02105-
dc.contributor.alternativeNameKim, Dong Ki-
dc.contributor.affiliatedAuthor김동기-
dc.contributor.affiliatedAuthor김한중-
dc.contributor.affiliatedAuthor박은철-
dc.contributor.affiliatedAuthor박형욱-
dc.contributor.affiliatedAuthor손명세-
dc.contributor.affiliatedAuthor송기준-
dc.citation.volume31-
dc.citation.number4-
dc.citation.startPage875-
dc.citation.endPage884-
dc.identifier.bibliographicCitationKorean Journal of Preventive Medicine (예방의학회지), Vol.31(4) : 875-884, 1998-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Humanities and Social Sciences (인문사회의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Preventive Medicine (예방의학교실) > 1. Journal Papers
3. College of Nursing (간호대학) > Dept. of Nursing (간호학과) > 1. Journal Papers

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