| Autor: |
Chan Zeng, Zhaoxing Pan, MaWhinney, Samantha, Barón, Anna E., Zerbe, Gary O. |
| Předmět: |
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| Zdroj: |
American Statistician; Feb2011, Vol. 65 Issue 1, p31-36, 6p |
| Abstrakt: |
We present a permutation approach to testing the linear hypothesis in multivariate general linear models, and apply it to the classical knee stiffness dataset of Ghosh, Grizzle, and Sen. We compare the permutation tests to commonly used approximations to the normal theory tests and conclude that among commonly available software, the SAS procedure GLM with the 'exact' option provides the best, albeit conservative, approximation. This article has supplemental material online. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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