High-dimensional repeated measures

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 o...

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Detalles Bibliográficos
Autores principales: Happ, Martin, Harrar, Solomon W., Bathke, Arne C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2017
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5546067/
https://www.ncbi.nlm.nih.gov/pubmed/28824350
http://dx.doi.org/10.1080/15598608.2017.1307792
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author Happ, Martin
Harrar, Solomon W.
Bathke, Arne C.
author_facet Happ, Martin
Harrar, Solomon W.
Bathke, Arne C.
author_sort Happ, Martin
collection PubMed
description 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).
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spelling pubmed-55460672017-08-17 High-dimensional repeated measures Happ, Martin Harrar, Solomon W. Bathke, Arne C. J Stat Theory Pract Articles 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). Taylor & Francis 2017-07-03 2017-03-17 /pmc/articles/PMC5546067/ /pubmed/28824350 http://dx.doi.org/10.1080/15598608.2017.1307792 Text en © 2017 Martin Happ, Solomon W. Harrar, and Arne C. Bathke. Published with license by Taylor & Francis http://creativecommons.org/licenses/by-nc-nd/4.0/ 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.
spellingShingle Articles
Happ, Martin
Harrar, Solomon W.
Bathke, Arne C.
High-dimensional repeated measures
title High-dimensional repeated measures
title_full High-dimensional repeated measures
title_fullStr High-dimensional repeated measures
title_full_unstemmed High-dimensional repeated measures
title_short High-dimensional repeated measures
title_sort high-dimensional repeated measures
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5546067/
https://www.ncbi.nlm.nih.gov/pubmed/28824350
http://dx.doi.org/10.1080/15598608.2017.1307792
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