General linear models for the analysis of single subject data and for the comparison of individuals

In longitudinal person-oriented and idiographic research, individual-specific parameter estimation is strongly preferred over estimation that is based on aggregated raw data. In this article, we ask whether methods of the General Linear Model, that is, repeated measures ANOVA and regression, can be...

Full description

Bibliographic Details
Main Authors: Alexander von Eye, Wolfgang Wiedermann
Format: Article
Language:English
Published: Lund University Library 2015-02-01
Series:Journal for Person-Oriented Research
Online Access:https://journals.lub.lu.se/jpor/article/view/20279
id doaj-2e52cacc5a3f424eb11d4eda38a995a8
record_format Article
spelling doaj-2e52cacc5a3f424eb11d4eda38a995a82020-11-25T02:11:04ZengLund University LibraryJournal for Person-Oriented Research2002-02442003-01772015-02-0111-210.17505/jpor.2015.07General linear models for the analysis of single subject data and for the comparison of individualsAlexander von Eye0Wolfgang Wiedermann1Michigan State UniversityUniversity of Vienna In longitudinal person-oriented and idiographic research, individual-specific parameter estimation is strongly preferred over estimation that is based on aggregated raw data. In this article, we ask whether methods of the General Linear Model, that is, repeated measures ANOVA and regression, can be used to estimate individual-specific parameters. Scenarios and corresponding design matrices are presented in which the shape of temporal trajectories of individuals is parameterized. Real world data examples and simulation results suggest that, for series of sufficient length, trajectories can be well described for individuals. In addition, scenarios are presented for the comparison of two individuals. Here again, trajectories can be well described and the statistical comparison of individuals is possible. However, in contrast to the power for the description of individual series, which is satisfactory, the power for the comparison of individuals is low (except when effect sizes are large). In all simulated scenarios, the power of tests increases only up to a certain number of observation points, and reaches a ceiling at this number. The fact that all parameters cannot always be estimated is also discussed, and options are presented that go beyond what standard general purpose software packages offer. https://journals.lub.lu.se/jpor/article/view/20279
collection DOAJ
language English
format Article
sources DOAJ
author Alexander von Eye
Wolfgang Wiedermann
spellingShingle Alexander von Eye
Wolfgang Wiedermann
General linear models for the analysis of single subject data and for the comparison of individuals
Journal for Person-Oriented Research
author_facet Alexander von Eye
Wolfgang Wiedermann
author_sort Alexander von Eye
title General linear models for the analysis of single subject data and for the comparison of individuals
title_short General linear models for the analysis of single subject data and for the comparison of individuals
title_full General linear models for the analysis of single subject data and for the comparison of individuals
title_fullStr General linear models for the analysis of single subject data and for the comparison of individuals
title_full_unstemmed General linear models for the analysis of single subject data and for the comparison of individuals
title_sort general linear models for the analysis of single subject data and for the comparison of individuals
publisher Lund University Library
series Journal for Person-Oriented Research
issn 2002-0244
2003-0177
publishDate 2015-02-01
description In longitudinal person-oriented and idiographic research, individual-specific parameter estimation is strongly preferred over estimation that is based on aggregated raw data. In this article, we ask whether methods of the General Linear Model, that is, repeated measures ANOVA and regression, can be used to estimate individual-specific parameters. Scenarios and corresponding design matrices are presented in which the shape of temporal trajectories of individuals is parameterized. Real world data examples and simulation results suggest that, for series of sufficient length, trajectories can be well described for individuals. In addition, scenarios are presented for the comparison of two individuals. Here again, trajectories can be well described and the statistical comparison of individuals is possible. However, in contrast to the power for the description of individual series, which is satisfactory, the power for the comparison of individuals is low (except when effect sizes are large). In all simulated scenarios, the power of tests increases only up to a certain number of observation points, and reaches a ceiling at this number. The fact that all parameters cannot always be estimated is also discussed, and options are presented that go beyond what standard general purpose software packages offer.
url https://journals.lub.lu.se/jpor/article/view/20279
work_keys_str_mv AT alexandervoneye generallinearmodelsfortheanalysisofsinglesubjectdataandforthecomparisonofindividuals
AT wolfgangwiedermann generallinearmodelsfortheanalysisofsinglesubjectdataandforthecomparisonofindividuals
_version_ 1724916496312827904