Hi, Georg,
I'm not certain that I would do a factor analysis with
your data. Your sample size is large enough to have a
an adequate variable-to-subject ratio. The variable
reduction techniques such PCA are useful primarily
when you need a data/variable reduction
technique--which doesn't seem to be the case here. In
addition, the factors/PCAs add interpretive
complexity. Moreover, it looks like you're extracting
a large number of factors--which is worrisome.
My inclination would be to fit your model with
individual variables---and to consider the use of
restricted cublic splines if your data warrant their
use.
No, I wouldn't include the "dependent" variable in a
factor analysis or PCA.
SR Millis
--- georg wernicke <[email protected]>
wrote:
> Dear SR Mills,
>
> thank you very much for your help. It is most
> appreciated. I am just
> going over the mentioned article, it seems as i have
> some
> collinearity. i dropped 2 variables which are
> indicated as collinear
> by the belsley threshold, the factortest immideately
> went up from 4 to
> 7 factors and will prob. improve once i have
> corrected for all
> possibly collinear variables.
>
> however, do i include the dependent variable in the
> factor equation?
> (e.g. factor dependent independent1 independent2
> etc..)
>
> and what do i get from knowing that the factor
> analysis gives me lets
> say 9 factors?
>
> once again, thanxs for your help
>
> george
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