The Analysis of Repeated Measurements with Mixed-Model Adjusted "F" Tests

Autor/inn/en	Kowalchuk, Rhonda K.; Keselman, H. J.; Algina, James; Wolfinger, Russell D.
Titel	The Analysis of Repeated Measurements with Mixed-Model Adjusted "F" Tests
Quelle	In: Educational and Psychological Measurement, 64 (2004) 2, S.224-242 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164403260196
Schlagwörter	Interaction; Sample Size; Statistical Analysis; Evaluation Methods; Error of Measurement + Suchen Sie Ihr Suchwort? Interaktion; Statistische Analyse; Messfehler
Abstract	One approach to the analysis of repeated measures data allows researchers to model the covariance structure of their data rather than presume a certain structure, as is the case with conventional univariate and multivariate test statistics. This mixed-model approach, available through SAS PROC MIXED, was compared to a Welch-James type statistic. The Welch-James approach is known to provide generally robust tests of treatment effects in a repeated measures between-by within-subjects design under assumption violations given certain sample size requirements. The mixed-model "F" tests were based on Kenward-Roger's adjusted degrees of freedom solution, an approach specifically proposed for small sample settings. The authors investigated Type I error control for repeated measures main and interaction effects in unbalanced designs when normality and covariance homogeneity assumptions did not hold. The mixed-model Kenward-Roger's adjusted "F" tests showed superior Type I error control in small sample size conditions in which the Welch-James type statistic was nonrobust; power rates, however, did not favor one approach over the other. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10