![]() ![]() ![]() ![]() ![]()
The leftmost section of this table shows the variance explained
by the initial solution.
Only three factors in the initial solution have eigenvalues greater
than 1.
Together, they account for almost 65% of the variability
in the original variables. This suggests that three latent influences
are associated with service usage, but there remains room for a lot
of unexplained variation.
The second section of this table shows the variance explained by the extracted
factors before rotation.
The cumulative variability explained by these three factors in the
extracted solution is about 55%, a difference of 10% from the initial
solution.
Thus, about 10% of the variation explained by the initial solution is lost due to latent
factors unique to the original variables and variability that simply cannot
be explained by the factor model.
The rightmost section of this table shows the variance explained by the extracted
factors after rotation.
The rotated factor model makes some small adjustments to factors 1 and 2, but
factor 3 is left virtually unchanged. Look for changes between the
unrotated and rotated factor matrices to see how the rotation affects the
interpretation of the first and second factors.
|
|
Total Variance Explained |