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| Titel: |
An f-test for multivariate repeated measures data with the wiener stochastic process pattern in the covariance matrix |
| Auteur: |
Diaz, Carroll J. Johnson, William D. |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 27 (1998) nr. 2 pagina's 275-289 |
| Jaar: |
1998 |
| Inhoud: |
In the analysis of repeated measures experiments certain patterns may arise in the structure of the covariance matrix.We can take advantage of these patterns when testing the equality of means hypothesis in that the patterned covariance matrix can be reduced to diagonal form.In estimating the parameters of the diagonal matrix, we get more degrees of freedom for our estimates because we have fewer parameters to estimate.This increase in degrees of freedom leads to a more powerful test of the equality of means hypothesis.One such pattern that is reducible to diagonal form is the Wiener Stochastic Process pattern.Assuming this pattern is present in the structure of the covariance matrix, maximum likelihood estimates of the mean and covariance matrices will be derived.Using these estimates, we derive an exact F-test of the equality of means hypothesis. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 3 van 16 gevonden artikelen
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