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  • 标题:A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models – The R Package pbkrtest
  • 本地全文:下载
  • 作者:Ulrich Halekoh ; Søren Højsgaard
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2014
  • 卷号:59
  • 期号:1
  • 页码:1-32
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic χ 2 test. Such tests can, however, be very poor for small and moderate sample sizes. The pbkrtest package implements two alternatives to such approximate χ 2 tests: The package implements (1) a Kenward-Roger approximation for performing F tests for reduction of the mean structure and (2) parametric bootstrap methods for achieving the same goal. The implementation is focused on linear mixed models with independent residual errors. In addition to describing the methods and aspects of their implementation, the paper also contains several examples and a comparison of the various methods.
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