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  • 标题:Type I Error Rates of the Kenward-Roger Adjusted Degree of Freedom F-test for a Split-Plot Design with Missing Values
  • 本地全文:下载
  • 作者:Padilla, Miguel A. ; Algina, James
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2007
  • 卷号:6
  • 期号:1
  • 页码:8
  • 出版社:Wayne State University
  • 摘要:The Type I error rate of the Kenward-Roger (KR) test, implemented by PROC MIXED in SAS, was assessed through a simulation study for a one between- and one within-subjects factor split-plot design with ignorable missing values and covariance heterogeneity. The KR test controlled the Type I error well under all of the simulation factors, with all estimated Type I error rates between .040 and .075. The best control was for testing the between-subjects main effect (error rates between .041 and .057) and the worst control was for the between-by-within interaction (.040 to .075). The simulated factors had very small effects on the Type I error rates, with simple effects in two-way tables no larger than .01.
  • 关键词:Missing values; Kenward-Roger F-test; Robustness; mixed models; split-plot design
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