An iterative process is proposed for obtaining an orthogonal simple structure solution. At each iteration, a target matrix is constructed such that the relative contributions of the target majorize the original ones, factor by factor. The convergence of the procedure is proven, and the algorithm is illustrated. (SLD)

The identification of two factors when one factor is expected is an artifact caused by using factor analysis on data that would be more appropriately analyzed with a unidimensional unfolding model. A numerical illustration is given, and ways to determine whether data conform to the unidimensional unfolding model are reviewed. (SLD)

A class of oblique rotation procedures is proposed to rotate a pattern matrix so that it optimally resembles a matrix that has an exact simple pattern. It is demonstrated that the method can recover relatively complex simple structures where other simple structure rotation techniques fail. (SLD)

Univocal varimax is an orthogonal factor rotation strategy aimed at improving upon the simple structure qualities of a preliminary varimax solution. This is accomplished by targetting for patterned rotation the highest element in each row of the varimax factor loading matrix. (Author)

It is shown that common factors are not subject to indeterminancy to the extent that has been claimed (Guttman, 1955), because the measure of indeterminancy that has been adopted is ill-founded. (Author/RC)

Shows that the Harris factors of R have psychometric properties similar to those discussed by Kaiser and Caffrey (1965) and Bentler (1968). Specifically it is shown that the Harris factors of R maximize a lower-bound to the reliability of a composite measure derived by Guttman (1945). (Author/RC)

Factor structures of student ratings of instruction resulting from total group, between group, and within group analyses were compared. Six factors obtained from responses by students to 31 items were used to approximate the between group covariance matrix based on 437 classroom means and the pooled within classroom covariance matrix. (Author/BJG)

Over the years, a number of rationales have been advanced to solve the problem of "blind" oblique factor transformation. By blind transformation is meant the transformation of orthogonal--and often interpretively ineffectual--factors to a position usually dictated by Thurstone's principles of simple structure, but not influenced by a…

Standard errors for maximum likelihood estimates of factor loadings are expressed in terms of the inverse of an augmented information matrix. This formulation arises naturally by viewing the problem as one in constrained maximum likelihood estimation. The constraints correspond to the form of rotation used. Results are given for canonical rotation…

A FORTRAN computer program was derived for an IBM series 360/370 computer system that provides a factor analytic solution for large three-dimensional data matrices. The computational procedures employed are based upon those presented in Method III by Tucker. (Author/JKS)

A computational algorithm, called the orthotran solution, is developed for determining oblique factor analytic solutions utilizing orthogonal transformation matrices. Selected results from illustrative studies are provided. (Author/JKS)

Demonstrates the value of spreadsheets for teaching sociology using Lotus 1 2 3 as an example. Shows how a Cholesky factorization, an eigenstructure solution, a correlation analysis, and a discriminant analysis may be performed using a spreadsheet or a BASIC program (included). (BSR)

A factor replication procedure (FACTOREP) was evaluated using four psychometrically equivalent synthetic correlation matrices containing an imposed three-subscale structure. Comparisons of the structure revealed by two, three, four, and nine-factor rotations using the FACTOREP showed that only the three factor solutions were replicable across all…

A generalized congruence maximization procedure for the case of m matrices is presented. The orthogonal rotation procedure simultaneously maximizes the sums of all coefficients of congruence between corresponding factors of m factor matrices. (NSF)

Order analysis, a technique to isolate unidimensional hierarchies representing multidimensional structure of binary data, is reviewed. Several theoretical flaws inherent in the probalistic version are presented. Suggestions of possible directions for future research are offered. (Author)