An iterative majorization algorithm is proposed for orthogonal congruence rotation that is guaranteed to converge from every starting point. In addition, the algorithm is easier to program than the algorithm proposed by F. B. Brokken, which is not guaranteed to converge. The derivation of the algorithm is traced in detail. (SLD)

A relatively simple technique for assessing the convergence of sets of variables across method domains is presented. The technique, two-step principal components analysis, empirically orthogonalizes each method domain into sets of components, and then analyzes convergence among components across domains. (Author)

Two proposed methods of factor analyzing a correlation matrix using only the off-diagonal elements are compared. The purpose of these methods is to avoid using the diagonal communality elements which are generally unknown and must be estimated. (Author/JKS)

Four prominent oblique transformation techniques--promax, the Harris-Kaiser procedure, biquartimin, and direct oblimin--are examined and compared. Additionally, two newly developed procedures are presented and included in the comparisons. (Author/RC)

Two computer subroutine packages for the analytic rotation of a factor matrix, A(p x m), are described. The first program uses the Flectcher (1970) gradient method, and the second uses the Polak-Ribiere (Polak, 1971) gradient method. The calculations in both programs involve the optimization of a function of free parameters. The result is a…

Applications to the Promax Rotation are discussed, and it is shown that these procedures solve Thurstone's hitherto intractable "invariant" box problem as well as other more common problems based on real data. (Author/RC)

Populations of factorially simple and complex data were generated with first the oblique and orthogonal factor models, and then solutions based on special cases of the general orthomax criterion were compared on the basis of these characteristics. The results are discussed and implications noted. (DEP)

Two population raw data matrices were constructed by computer simulation techniques. Each consisted of 10,000 subjects and 12 variables, and each was constructed according to an underlying factorial model consisting of four major common factors, eight minor common factors, and 12 unique factors. The computer simulation techniques were employed to…