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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 제6권 제1호
- 발행연도
- 2004.1
- 수록면
- 71 - 87 (17page)
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초록· 키워드
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Mixed models are frequently used in inference for the repeated measurement data of biological and biomedical studies. In this paper, we consider the efficiency of the estimated generalized least squares estimator for the linear mixed model. We find that it works well with respect to consistency and empirical efficiency and has similar precision with the generalized least squares estimator. For the nonlinear mixed model, we notice that the approximate extended least squares estimator based on linearization may have serious bias in mean parameter estimates, especially when the variability in random coefficients is large. On the other hand, the extended least squares estimator using Monte Carlo method produces estimates close to that of exact extended least squares estimator and both procedures yield good estimates and confidence intervals for the mean parameters.
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참고문헌 (11)
참고문헌 신청
/ 1980 / Evaluation of methods for estimating population pharmacokinetic parameters I Journal of Pharmacokinetics and Biopharmaceutics : 553 ~ 571
/ 1980195-222 / CRC Critical Reviews in Biomedical Engineering
/ 1984 / Asymptotic properties of optimization estimators for the independent not identically distributed case with application to extended least squares estimators Division
/ 1985 / Methodology of population pharmacokinetics : 135 ~ 183
/ 1990 / Nonlinear mixed effects models for repeated measures data 46 : 673 ~ 687
/ 1980195-222 / CRC Critical Reviews in Biomedical Engineering
/ 1984 / Asymptotic properties of optimization estimators for the independent not identically distributed case with application to extended least squares estimators Division
/ 1985 / Methodology of population pharmacokinetics : 135 ~ 183
/ 1990 / Nonlinear mixed effects models for repeated measures data 46 : 673 ~ 687
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