varimax rotation difference between R and SPSS

Andreas Cordes <andreas.cordes at stud.uni-goettingen.de> writes:

Hi,
I am puzzeled with a differing result of princomp in R and FACTOR in 
SPSS. Regarding the amount of explained Variance, the two results are 
the same. However, the loadings differ substantially, in the unrotated 
as well as in the rotated form.
In both cases correlation matrices are analyzed. The sums of the squared 
components is one in both programs.
Maybe there is an obvious reason, but I somehow fail to see it.

I get

SPSS.res/ R.res

V2        V3
1  2.315960 -1.461720
2  2.315960 -1.461720
3  2.315960 -1.461720
4  2.315960 -1.461720
5  2.315960 -1.461720
6  2.315960 -1.461719
7  2.315960 -1.461720
8  2.315960 -1.461720
9  2.315960 -1.461719
10 2.315960 -1.461720
11 2.315960 -1.461720
12 2.315960 -1.461720
13 2.315960 -1.461719
14 2.315960 -1.461720

which I presume is part of the puzzle. I don't think varimax() wants
its loadings normalized like they are in loadings(princomp())
(after all, it was designed for factanal(), not princomp()), and I
wouldn't be the least surprised if the $sdev components of princomp()
were related to  2.315960 and 1.461720.

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