Journal
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT
Volume 64, Issue 2, Pages 224-242Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0013164403260196
Keywords
repeated measurements; mixed-model analyses; Welch-James adjusted-df test; Kenward-Roger's adjusted-df test; small sample settings
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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.
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