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  • 标题:Type I Error Rates of the Kenward-Roger F-test for a Split-Plot Design with Missing Values and Non-Normal Data
  • 本地全文:下载
  • 作者:Padilla, Miguel A. ; Min, YoungKyoung ; Zhang, Guili
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2008
  • 卷号:7
  • 期号:2
  • 页码:4
  • 出版社:Wayne State University
  • 摘要:The Type I error of the Kenward-Roger (KR) F-test was assessed through a simulation study for a between- by within-subjects split-plot design with non-normal ignorable missing data. The KR-test for the between- and within-subjects main effect was robust under all simulation variables investigated and when the data were missing completely at random (MCAR). This continued to hold for the between-subjects main effect when data were missing at random (MAR). For the interaction, the KR F-test performed fairly well at controlling Type I under MCAR and the simulation variables investigated. However, under MAR, the KR F-test for the interaction only provided acceptable Type I error when the within-subjects factor was set at 3 and 5% missing data.
  • 关键词:missing values; Kenward-Roger F-test; robustness; mixed models; split-plot design; non-normal data; and covariance heterogeneity
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