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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제21권 제4호
- 발행연도
- 2019.1
- 수록면
- 1,655 - 1,663 (9page)
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This paper proposes using hierarchical-likelihood estimation method for binary panel data models featuring state dependence and unmeasured heterogeneity. Hierarchical generalized linear models are an extension of generalized linear models in that they combine generalized linear models with random effects. Hierarchical likelihood based upon hierarchical generalized linear models provides a useful tool for analyzing multivariate data with correlation. These models allow various regression models for mean parameters of response variable as well as dispersion parameters. For a inference, the hierarchical- likelihood approach is suggested for a useful too as model selection and residual plots with real data analysis. In this paper, we suggest hierarchical-likelihood approach estimators for binary random effects-models, and show that this approach outperforms existing marginal likelihood estimators at low computation cost by simulation studies. And then, we add its usefulness by analyzing a real example.
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참고문헌 (20)
참고문헌 신청
Baltagi, B. H. / 2001 / Econometric analysis of panel data / John Wiley & Sons
Bellamy, S. L. / 2000 / Analysis of dichotomous outcome data for community intervention studies / Statistical Methods in Medical Research 9(2):135~159
Breslow, N. E. / 1993 / Approximate inference in generalized linear mixed models / Journal of The American Statistical Association 88(421):9~25
Cox, D. R. / 1987 / Parameter orthogonality and approximate conditional inference (with discussion) / Journal of The Royal Statistical Society, Series B 49(1):1~39
Diggle, P. / 1994 / Analysis of longitudinal data / Clarendon Press
Bellamy, S. L. / 2000 / Analysis of dichotomous outcome data for community intervention studies / Statistical Methods in Medical Research 9(2):135~159
Breslow, N. E. / 1993 / Approximate inference in generalized linear mixed models / Journal of The American Statistical Association 88(421):9~25
Cox, D. R. / 1987 / Parameter orthogonality and approximate conditional inference (with discussion) / Journal of The Royal Statistical Society, Series B 49(1):1~39
Diggle, P. / 1994 / Analysis of longitudinal data / Clarendon Press
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