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  • 标题:A score test for variance components in a semiparametric mixed-effects model under non-normality
  • 本地全文:下载
  • 作者:Yan Sun ; Jin-Ting Zhang
  • 期刊名称:Statistics and Its Interface
  • 印刷版ISSN:1938-7989
  • 电子版ISSN:1938-7997
  • 出版年度:2011
  • 卷号:4
  • 期号:1
  • 页码:65-72
  • DOI:10.4310/SII.2011.v4.n1.a7
  • 出版社:International Press
  • 摘要:In this paper, we propose a score test for variance components in a semiparametric mixed-effects model when the random-effects and measurement errors are not normally distributed. The asymptotic null distribution of the test statistic is shown to be a simple chi-squared distribution with the degrees of freedom being the number of linearlyindependent variance components. The simulation results show that the proposed score test is robust against the nonnormality of the random-effects and the measurement errors and performs well in terms of both size and power. The score test is illustrated via an application to a real longitudinal data set collected in a clinical trial study.
  • 关键词:extended quasi-likelihood; Laplace approximation; local linear smoothing; score test; semiparametric mixed-effects model; variance components
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