Effect Size
Some suggest the use of eigenvalues as effect size measures, however, this is generally not supported. Instead, the canonical correlation is the preferred measure of effect size. It is similar to the eigenvalue, but is the square root of the ratio of SSbetween and SStotal. It is the correlation between groups and the function. Another popular measure of effect size is the percent of variance for each function. This is calculated by: (λx/Σλi) X 100 where λx is the eigenvalue for the function and Σλi is the sum of all eigenvalues. This tells us how strong the prediction is for that particular function compared to the others. Percent correctly classified can also be analyzed as an effect size. The kappa value can describe this while correcting for chance agreement.
Read more about this topic: Discriminant Function Analysis
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