期刊文献+

线性混合模型中方差分量的广义推断 被引量:1

Generalized Inferences on the Variance Components in General Linear Mixed Model
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摘要 本文考虑了线性混合模型中方差分量的假设检验和区间估计问题.基于广义p-值和广义置信区间的概念,构造了对应于随机效应的单个方差分量的精确检验和置信区间.所构造的广义p-值和广义置信区间是最小充分统计量的函数.对于两个独立线性混合模型中对应于随机效应的方差分量的比较,建立了精确检验和置信区间.进一步,研究了所给检验和置信区间的统计性质,给出了这些检验方法与文献中已有方法的功效比较的模拟结果.模拟结果表明,新检验在功效方面有显著的改进.最后,通过一个实例来演示本文方法. In this paper,we consider the problems of hypothesis testing and interval estimation for variance components in general linear mixed model.Exact test and confidence interval for a single variance component corresponding to random effect are developed based on the concepts of generalized p-value and generalized confidence interval.The generalized p-values and generalized confidence intervals we have developed are functions of the minimal sufficient statistics.Exact test and confidence interval are also established for comparing the random-effects variance components in two independent general linear mixed models. Furthermore,we investigate the statistical properties of the resulting tests and confidence intervals.Some simulation results to compare the powers of the proposed test with those of the existing method are reported.The simulation results indicate that new test appears to have significant gain in the power.Finally,the proposed methods are demonstrated by a real example
出处 《应用数学学报》 CSCD 北大核心 2010年第1期1-11,共11页 Acta Mathematicae Applicatae Sinica
基金 国家自然科学基金数学天元青年基金(10926059) 北京市属市管高等学校人才强教计划(0506011200702) 浙江省教育厅科研项目(Y200803920) 杭州电子科技大学科研启动基金(KYS025608094)资助项目
关键词 广义P-值 广义置信区间 方差分量 线性混合模型 generalized p-value generalized confidence interval variance component linear mixed model
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  • 1G. A. Milliken and D. E. Johnson, Analysis of Messy Data (Vol. I), Life Learning Publications, Belmont, 1984.
  • 2L. Zhou and T. Mathew, Some tests for variance components using generalized p values, Technometrics, 1994, 36(4): 394-402.
  • 3D. W. Webb and S. A. Wilkerson, Use of generalized p values to compare two independent estimates of tube-to-tube variability for the M1A1 tank, in Proceedings of the Section on Physical and Engineering Sciences, American Statistical Association, 1999, 105-109.
  • 4T. Mathew and D. W. Webb, Generalized p values and confidence intervals for variance components: applications to army test and evaluation, Technometrics, 2005, 47(3):312-322.
  • 5K. W. Tsui and S. Weerahandi, Generalized p-values in significance testing of hypotheses in the presence of nuisance parameters, J. Amer. Statist. Assoc., 1989, 84(406): 602-607.
  • 6S. Weerahandi, Generalized confidence intervals, J. Amer. Statist. Assoc., 1993, 88(423): 899-905.
  • 7S. Weerahandi. Exact Statistical Methods for Data Analysis, Springer-Verlag, New York, 1995.
  • 8M. X. Wu and S. G. Wang, A new spectral decomposition for the covariance matrix in linear mixed model and its applications, Science in China (Series A), 2005, 35(8): 947-960.
  • 9S. G. Wang and S. C. Chow, Advanced Linear Model, Marcel Dekker, New York, 1994.
  • 10S. S. Mao, J. L. Wang, and X. L. Pu, Advanced Mathematical Statistics, Higher Education Press, Beijing, 1998.

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  • 1BENNET B M. Note on a solution of the generalized Behrens-Fisher problem[J]. Annals of the Institute of Statistical Mathematics, 1951,2 : 87-90.
  • 2JAMES G S. Test of linear hypotheses in univariate and multivariate analysis when the ratios of the popu- lation variances are known[J]. Biometrika, 1954, 41 : 19-43.
  • 3KIM S. A practical solution to the multivariate Beh- rens-Fisher problem [J]. Biometrika, 1992, 79: 171- 176.
  • 4CHRISTENSEN W F,RENCHER A C. A comparison of type I error rates and power levels for several solu- tions to the multivariate Behrens-Fisher problem[J]. Communications in Statistics-Simulation and Computa- tion, 1997,26 :1251-1273.
  • 5JOHNSON R A,WEERAHANDI S. A Bayesian solu- tion to the multivariate Behrens-Fisher problem[J]. Bi- ometrika, 1998,83 : 145-149.
  • 6GAMAGE J, MATHEW T, WEERAHANDI S. Gen- eralized p-values and generalized confidence regions for the mul VA[J] 177-189 ivariate Behrens-Fisher problem and MANO- Journal of Multivariate Analysis, 2004, 88.177-189.
  • 7TUSI K W, WEERAHANDI S. Generalized p-values in significance testing of hypotheses in the presence of nuisance parameters[J]. Journal of the American Sta- tistical Association, 1989,84:602-607.
  • 8WEERHANDI S. Testing regression equality with un- equal variances [J ]. Econometrica, 1987, 55: 1211- 1215.
  • 9WEERAHANDI S. Testing variance components in mixed models with generalized p-values[J]. Journal of the American Statistical Association, 1991, 86: 151- 153.
  • 10WEERAHANDI S. Exact Statistical Methods for Da- ta Analysis[M]. New York.. np, 1995.

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