Table 2.
Significance of CCA variate pairs
| CCA | Canonical Correlation | Squared Canonical Correlation | Eigenvalue | Wilk’s Lambda | F(num df, den df) | p-value | Jackknife criteria met? |
|---|---|---|---|---|---|---|---|
| GMV | |||||||
|
| |||||||
| Pair 1 | .54 | .29 | .41 | .14 | 1.4 (952, 8243.7) | < .001 | yes |
| Pair 2 | .46 | .22 | .28 | .19 | 1.2 (871,768.1) | < .001 | yes |
|
| |||||||
| CT | |||||||
|
| |||||||
| Pair 1 | .56 | .31 | .45 | .15 | 1.3 (952, 8243.7) | < .001 | yes |
| Pair 2 | .49 | .24 | .32 | .22 | 1.1 (871,768.1) | .01 | yes |
|
| |||||||
| CSA | |||||||
|
| |||||||
| Pair 1 | .54 | .29 | .40 | .15 | 1.3 (952, 8243.7) | < .001 | yes |
| Pair 2 | .46 | .21 | .27 | .21 | 1.2 (871,768.1) | .002 | yes |
|
| |||||||
| LGI | yes | ||||||
|
| |||||||
| Pair 1 | .54 | .3 | .42 | .15 | 1.2 (952, 7791) | < .001 | yes |
Table shows significant results for latent pairs of each CCA analysis and information about the jackknife criteria. CCA = canonical correlation analysis; GMV = Volume Analysis; CT= Cortical Thickness Analysis; CSA= Surface Area Analysis; LGI= Gyrification Analysis.