So I ran a factor analysis (principal components method) on a dataset, first using the correlation matrix and then using the covariance matrix, both with varimax rotations. The results of both factor analyses indicate nearly identical first and second factors, and somewhat different third and fourth factors.
I am curious if this could be interpreted as factors 3 & 4 not being useful? Or that only the first two factors are appropriate for analysis? Or is this just showing a pattern in the correlation/covariance structures of my data (i.e. correlated correlations/covariances?)