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Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions

Huynh, Huynh, Feldt, Leonard S.·1970·Journal of the American Statistical Association

Abstract

Investigation is made of the character of the covariance matrix which will result in exact F-distributions for the treatments and interaction variance ratios in repeated measurements designs. It is shown, assuming multivariate normality, that the matrix may exhibit a more general character than is typically implied to be essential. Equality of variances and equality of covariances, with identical matrices for all levels of a second treatment factor, are sufficient but not necessary conditions. The necessary and sufficient condition is the equality of variances of differences for all pairs of treatment measures assumed to be correlated. An alternative statement is that the Box-Geisser-Greenhouse parameter ε = 1.0. A test is described which bears on the tenability of this condition.

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Crossref · 10.1080/01621459.1970.10481187

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Metadata

Authors
Huynh, H., & Feldt, L. S.
Venue
Journal of the American Statistical Association
Published
1970-12
Volume
65
Issue
332
Pages
1582-1589
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W1976429900
Cited by
946
References
1
FWCI
1.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions. https://app.cochat.ai/papers/10.1080/01621459.1970.10481187
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Huynh, H., & Feldt, L. S. (1970). Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1970.10481187

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