Journal of Statistical Theory and Practice

, Volume 11, Issue 3, pp 468–477 | Cite as

High-dimensional repeated measures

  • Martin Happ
  • Solomon W. Harrar
  • Arne C. BathkeEmail author
Open Access


Recently, new tests for main and simple treatment effects, time effects, and treatment by time interactions in possibly high-dimensional multi-group repeated-measures designs with unequal covariance matrices have been proposed. Technical details for using more than one between-subject and more than one within-subject factor are presented in this article. Furthermore, application to electroencephalo-graphy (EEG) data of a neurological study with two whole-plot factors (diagnosis and sex) and two subplot factors (variable and region) is shown with the R package HRM (high-dimensional repeated measures).


Analysis of variance factorial design heteroscedasticity profile analysis R package 

AMS Subject Classification



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Copyright information

© Grace Scientific Publishing 2017

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Martin Happ
    • 1
  • Solomon W. Harrar
    • 2
  • Arne C. Bathke
    • 1
    • 2
    Email author
  1. 1.Department of MathematicsUniversity of SalzburgSalzburgAustria
  2. 2.Department of StatisticsUniversity of KentuckyLexingtonUSA

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