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과대산포가 존재하는 이항형 자료의 회귀분석방법

Other Titles
 Regression Methods for Overdispersed Dichotomous Response Data 
 김동기  ;  한무영  ;  전우택  ;  명성민  ;  송기준 
 Journal of the Korean Neuropsychiatric Association (신경정신의학), Vol.44(5) : 549-552, 2005 
Journal Title
 Journal of the Korean Neuropsychiatric Association (신경정신의학) 
Issue Date
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.
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
3. College of Nursing (간호대학) > Dept. of Nursing (간호학과) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Medical Education (의학교육학과) > 1. Journal Papers
Yonsei Authors
Kim, Dong Ki(김동기)
Myoung, Sung Min(명성민)
Song, Ki Jun(송기준) ORCID logo https://orcid.org/0000-0003-2505-4112
Jeon, Woo Taek(전우택) ORCID logo https://orcid.org/0000-0002-9213-6057
Han, Moo Young(한무영)
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