지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제12권 제1호
- 발행연도
- 2010.1
- 수록면
- 17 - 27 (11page)
이용수
초록· 키워드
오류제보하기
Clustered data may have not only a correlation within-cluster but also a heterogeneity between-cluster. Thus, various random-effect models including generalized linear mixed models(GLMMs) have been widely used. However, the analysis of heterogeneity has been less studied. For this the prediction of random effects is very useful. In this paper we show a general framework how to model the clustered binominal data, and to estimate parameters and to predict random effects via SAS PROC NLMIXED. Thus, we illustrate the analyses with a real data set obtained from different 8 clinics for investigating a treatment effect. We demonstrate using this data set how an appropriate model can be selected via well-known model-selection criteria. We also present a plot on predicted random effects for investigating practically a potential heterogeneity over clinics.
목차
등록된 정보가 없습니다.
참고문헌 (23)
참고문헌 신청
Akaike, H. / 1973 / Information theory and an extension of the maximum likelihood principle, In: 2nd International Symposium on Information Theory / Akademiai Kiado : 267 ~ 281
Beitler, P. J. / 1985 / A mixed-effects model for categorical data / Biometrics 41 : 991 ~ 1000
Booth, J. G. / 1998 / Standard errors of prediction in generalized linear mixed models / Journal of the American Statistical Association 93 : 262 ~ 272
Breslow, N. E. / 1993 / Approximate inference in generalized linear mixed models / Journal of the American Statistical Association 88 : 9 ~ 25
Goldstein, H. / 2003 / Multilevel statistical models, 3rd edn / Arnold
Beitler, P. J. / 1985 / A mixed-effects model for categorical data / Biometrics 41 : 991 ~ 1000
Booth, J. G. / 1998 / Standard errors of prediction in generalized linear mixed models / Journal of the American Statistical Association 93 : 262 ~ 272
Breslow, N. E. / 1993 / Approximate inference in generalized linear mixed models / Journal of the American Statistical Association 88 : 9 ~ 25
Goldstein, H. / 2003 / Multilevel statistical models, 3rd edn / Arnold
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Analysis of Clustered Binominal Data Using Logistic-GLMMs
Journal of The Korean Data Analysis Society
2009 .01
-
A HGLM Approach for Clustered Insurance Claim Data
Journal of The Korean Data Analysis Society
2009 .01
-
On the Silhouette Plot in Cluster Analysis
Journal of The Korean Data Analysis Society
2009 .01
-
Analysis of Multivariate Binary Random Effect Models using Hierarchical Likelihood Approach
Journal of The Korean Data Analysis Society
2019 .01
-
Inference for heterogeneity of treatment effect in multi-center clinical trial
한국데이터정보과학회지
2011 .06
-
Modeling of random effects covariance matrix in marginalized random effects models
한국데이터정보과학회지
2016 .06
-
On prediction of random effects in Log-normal frailty models
한국데이터정보과학회지
2009 .02
-
On Estimation of Random Effect in Poisson HGLMs
한국데이터정보과학회지
2008 .03
-
A Proportional Odds Mixed - Effects Model for Ordinal Data
한국데이터정보과학회지
2007 .06
이 논문의 저자 정보
최근 본 자료
댓글(0)
0