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Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions
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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“In order to compensate for such adverse effects in tests of within effects or between-within interactions, the noncentrality parameter and the degrees of freedom of the F distribution can be multiplied by a correction factor (Geisser & Greenhouse, 1958;Huynh & Feldt, 1970).”
From G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences (2007) · cites this paper as Huynh & Feldt, 1970
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Metadata
- Authors
- Huynh, H., & Feldt, L. S.
- Affiliations
- University of Iowa (US)
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1970-12
- Volume
- 65
- Issue
- 332
- Pages
- 1582-1589
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1976429900
- Cited by
- 945
- References
- 18
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 5 · 2023: 9 · 2022: 9 · 2021: 13 · 2020: 16 · 2019: 17 · 2018: 17 · 2017: 18 · 2016: 25 · 2015: 19 · 2014: 29 · 2013: 24 · 2012: 28
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- repeated measures designs, covariance matrix, multivariate normality, equality of variances, variance ratio
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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