I came across this in the Wikipedia page about Factor Analysis. Is that true that direct oblimin rotation results in greater eigen values? If that is true, what's the reason behind it and does it generalize to other oblique rotations ? (to avoid any confusions consider we only consider PCA as the factor extraction methods)
Because oblique methods don't constrain the factors to be orthogonal. There does tend to be confusion about what names are given to each part of the output in factor analysis, with different programs (e.g.
R) using different terms.
R doesn't seem to output anything called eigenvalues (as far as I can see from the help, anyway).