Magenta wrote:
> Why a factor analysis and not a principal components analysis? I've been
> taught that a principal components analysis makes fewer assumptions on the
> data, so
> assuming that one can perform a factor analysis then automatically one can
> also perform a principal components analysis.
>
> I think I have a preference for orthogonal rotations.
PCA explains variance. FA explains covariance.
Re orthogonal rotations, do you have reason to believe the factors will be
orthogonal? Few factors in the social sciences are completely orthogonal. Why
not try to reflect reality by allowing correlated factors?
(Of course, I too am revealing the bias of *my* training!)
Lise DeShea, Ph.D.
University of Kentucky
Educational/Counseling Psychology Dept.
245 Dickey Hall
Lexington KY 40506-0017
[EMAIL PROTECTED]
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