Permuting longitudinal data in spite of the dependencies

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• 作者：Sarah Friedrich^a ; ^{sarah.friedrich@uni-ulm.de} ; Edgar Brunner^b ; Markus Pauly^a
• 关键词：primary ; 62G10 ; secondary ; 62G09 ; 62H15 ; 62P10
• 刊名：Journal of Multivariate Analysis
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：153
• 期：Complete
• 页码：255-265
• 全文大小：468 K
• 卷排序：153

文摘

For general repeated measures designs the Wald-type statistic (WTS) is an asymptotically valid procedure allowing for unequal covariance matrices and possibly non-normal multivariate observations. The drawback of this procedure is its poor performance for small to moderate samples, i.e., decisions based on the WTS may become quite liberal. It is the aim of the present paper to improve the small-sample behavior of the WTS by means of a novel permutation procedure. In particular, it is shown that a permutation version of the WTS inherits its good large-sample properties while yielding a very accurate finite-sample control of the type-I error as shown in extensive simulations. Moreover, the new permutation method is motivated by a practical data set of a split plot design with a factorial structure on the repeated measures.