| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 418008 | Computational Statistics & Data Analysis | 2008 | 10 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Leo Knüsel,