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).
Document Type
Article
Publication Date
4-21-2017
Digital Object Identifier (DOI)
https://doi.org/10.1080/15598608.2017.1307792
Related Content
The research was supported by Austrian Science Fund (FWF) I 2697-N31.
Repository Citation
Happ, Martin; Harrar, Solomon W.; and Bathke, Arne C., "High-Dimensional Repeated Measures" (2017). Statistics Faculty Publications. 25.
https://uknowledge.uky.edu/statistics_facpub/25
Notes/Citation Information
Published in Journal of Statistical Theory and Practice, v. 11, no. 3, p. 468-477.
© 2017 Martin Happ, Solomon W. Harrar, and Arne C. Bathke. Published with license by Taylor & Francis
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.