Table 2.
Principal Component Analysis extracted a Rotated Component Matrix with 4 Components for the analysis that included behavioral variables from the stimulus interval. The matrix contains the principal component loadings, which are essentially bivariate correlation coefficients representing correlation between the variable (row) and the component (column). Only major loadings (larger than 0.25) are shown.
Rotated Component Matrix (Stimulus interval)
| Component
|
||||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| swimming | .928 | |||
| leap | .788 | |||
| erratic | .820 | |||
| thrashing towards | .827 | |||
| jumping | −.591 | |||
| near stimulus | .869 | |||
| bottom | .372 | .649 | ||
| immobility | −.941 | |||
| Ambulation score | .418 | −.521 | ||
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 6 iterations.