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과대산포가 존재하는 이항형 자료의 회귀분석방법
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김동기 | - |
dc.contributor.author | 명성민 | - |
dc.contributor.author | 송기준 | - |
dc.contributor.author | 전우택 | - |
dc.contributor.author | 한무영 | - |
dc.date.accessioned | 2017-10-26T05:56:43Z | - |
dc.date.available | 2017-10-26T05:56:43Z | - |
dc.date.issued | 2005 | - |
dc.identifier.issn | 1015-4817 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/150533 | - |
dc.description.abstract | In neuropsychiatrical research, many problems of statistical inference concern the relationship between the PTSD and traumatic experiences. The logistic model is widely used for modeling a relationship between the covariate and the magnitude of the PTSD. A common complication in the logistic model for dichotomous response data is overdispersion. In this study, two different methods for analyzing dichotomous response data are illustrated and compared. One method is the logistic regression approach, where the numbers of dichotomous responses are predicted by the logistic function of covariates. The other one is the overdispersed logistic regression approach, where the overdispersion is measured by a scale parameter in the variance function of the dichotomous response. In dichotomous response model, when reponses are overdispersed, the overdispersed logistic regression produces more appropriate standard errors of the regression coefficients and the 95% confidence intervals of odds ratios. Therefore, in neuropsychiatrical research, it is recommended to examine the overdispersion problems for their data set before applying the logistic regression model. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.language | Korean | - |
dc.publisher | 대한신경정신의학회 | - |
dc.relation.isPartOf | Journal of the Korean Neuropsychiatric Association (신경정신의학) | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.title | 과대산포가 존재하는 이항형 자료의 회귀분석방법 | - |
dc.title.alternative | Regression Methods for Overdispersed Dichotomous Response Data | - |
dc.type | Article | - |
dc.publisher.location | Korea | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.college | College of Nursing (간호대학) | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) | - |
dc.contributor.department | Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) | - |
dc.contributor.department | Dept. of Nursing (간호학과) | - |
dc.contributor.department | Dept. of Medical Education (의학교육학과) | - |
dc.contributor.department | Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) | - |
dc.contributor.googleauthor | 김동기 | - |
dc.contributor.googleauthor | 한무영 | - |
dc.contributor.googleauthor | 전우택 | - |
dc.contributor.googleauthor | 명성민 | - |
dc.contributor.googleauthor | 송기준 | - |
dc.identifier.doi | OAK-2005-05190 | - |
dc.contributor.localId | A00399 | - |
dc.contributor.localId | A01349 | - |
dc.contributor.localId | A02016 | - |
dc.contributor.localId | A03538 | - |
dc.contributor.localId | A04278 | - |
dc.relation.journalcode | J01837 | - |
dc.contributor.alternativeName | Kim, Dong Ki | - |
dc.contributor.alternativeName | Myoung, Sung Min | - |
dc.contributor.alternativeName | Song, Ki Jun | - |
dc.contributor.alternativeName | Jeon, Woo Taek | - |
dc.contributor.alternativeName | Han, Moo Young | - |
dc.citation.volume | 44 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 549 | - |
dc.citation.endPage | 552 | - |
dc.identifier.bibliographicCitation | Journal of the Korean Neuropsychiatric Association (신경정신의학), Vol.44(5) : 549-552, 2005 | - |
dc.date.modified | 2017-05-04 | - |
dc.identifier.rimsid | 42812 | - |
dc.type.rims | ART | - |
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