High-dimensional repeated measures

Martin Happ, Solomon W. Harrar, Arne C. Bathke

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Recently, new tests for main and simple treatment effects, time effects, and treatment by time interactions in possibly high-dimensional multigroup 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 electroencephalography (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).

Original languageEnglish
Pages (from-to)468-477
Number of pages10
JournalJournal of Statistical Theory and Practice
Volume11
Issue number3
DOIs
StatePublished - Jul 3 2017

Bibliographical note

Funding Information:
The research was supported by Austrian Science Fund (FWF) I 2697-N31.

Publisher Copyright:
© 2017 Martin Happ, Solomon W. Harrar, and Arne C. Bathke. Published with license by Taylor & Francis.

Keywords

  • Analysis of variance
  • R package
  • factorial design
  • heteroscedasticity
  • profile analysis

ASJC Scopus subject areas

  • Statistics and Probability

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