
Varimax Method. An orthogonal rotation method that
minimizes the number of variables that have high loadings on each
factor. It simplifies the interpretation of the factors.

Direct Oblimin
Method. A method for oblique
(nonorthogonal) rotation. When delta equals 0 (the default), solutions
are most oblique. As delta becomes more negative, the factors become
less oblique. To override the default delta of 0, enter a number less
than or equal to 0.8.

Quartimax Method.
A rotation method that
minimizes the number of factors needed to explain each variable. It
simplifies the interpretation of the observed variables.

Equamax Method. A rotation method that is a combination of
the varimax method, which simplifies the factors, and the quartimax
method, which simplifies the variables. The number of variables that
load highly on a factor and the number of factors needed to explain a
variable are minimized.

Promax Rotation. An oblique rotation, which allows factors
to be correlated. It can be calculated more quickly than a direct
oblimin rotation, so it is useful for large datasets.

end quote.
Thank you for the nice response,
I kmow that in practice transposing
the matrix is a common, but do not think
of it as a very valid approach. (Higher order) Factor analysis with oblique
rotation
and restrictions penalizing nonzero loadings would sound good for
me. Would
you know of any references for such
an approach?
Wolfgang
In SPSS all of the few dozen Proximity (similarity measures)
can be applied to variables. (After the data are transformed and
transposed) The Proximity matrix can then be read into the variety of
cluster procedures. Or the transposed data can be read directly into
the CLUSTER, or Quick cluster procedure. I see no reason (given that
you want to cluster variables) that the TWOSTEP cluster could not read
a transposed data matrix.
Of course there are all of the varieties of factor analysis which are
more commonly used to group variables. The CATPCA procedure factors
categorical variables.
When the variables are used to classify or differentiate a categorical
variable, there are procedures like DISCRIMINANT or the various