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Some Approximate Tests for Repeated Measurement Designs

Published online by Cambridge University Press:  01 January 2025

Huynh Huynh*
Affiliation:
University of South Carolina
*
Requests for reprints should be sent to Huynh Huynh, College of Education, University of South Carolina, Columbia, South Carolina 29208.

Abstract

Four approximate tests are considered for repeated measurement designs in which observations are multivariate normal with arbitrary covariance matrices. In these tests traditional within-subject mean square ratios are compared with critical values derived from F distributions with adjusted degrees of freedom. Two of them—the ∈ approximate and the improved general approximate (IGA) tests-behave adequately in terms of Type I error. Generally, the IGA test functions better than the ∈ approximate test, however the latter involves less computations. In regards to power, the IGA test may compete with one multivariate procedure when the assumptions of the latter are tenable.

Type
Original Paper
Copyright
Copyright © 1978 The Psychometric Society

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Footnotes

The author wishes to thank Garrett K. Mandeville for his careful reading of the final version of the paper.

References

Reference Note

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