Chisquare as a rotation criterion in factor analysis

The rotation problem in factor analysis consists in finding an orthogonal transformation of the initial factor loadings so that the rotated loadings have a simple structure that can be easily interpreted. The most popular orthogonal transformations are the quartimax and varimax procedures with Kaiser normalization. A classical chisquare contingency measure is proposed as a rotation criterion. It is claimed that this is a very natural criterion, not only for rotations but also for oblique transformations, that is not to be found in our popular statistical packages up to now.