The possibility of using a Q-analysis also for nominal data is discussed, using the J-index as a measure of similarity between persons. An example is given when ten persons sorted 16 playing cards into as many groups as they wished. A Q-analysis of these data gave a natural two-dimensional structure. (Author/BW)

A model for four-mode component analysis is developed and presented. The developed model, which is an extension of Tucker's three-mode factor analytic model, allows for the simultaneous analysis of all modes of a four-mode data matrix and the consideration of relationships among the modes. (Author/JKS)

It is proved for the common factor model that, under certain conditions maintaining the distinctiveness of each factor, a given factor will be determinate if there exists an unlimited number of variables in the model, each having an absolute correlation with the factor greater than some arbitrarily small quantity. (Author/JKS)

The G index and its generalizations in the six basic factor analytic designs are discussed. G should be used if there is no mutual direction of all the variables. G should also be used if the scale center is more suitable as a reference point than the mean value. (Author/CTM)

In response to works by Robert J. Sternberg, summarizes relations between components and factors as analytical tools for research on intelligence and mental abilities. (GC)

In oblique rotation of factor analyses, a variety of methods is possible. The direct oblimin method is one such rotation. The direct oblimin method requires setting a value for a parameter called gamma. This article explores problems with choosing gamma values and clarifies the results obtained at various gamma levels. (JKS)

The nine subtests of the Stanford Achievement Test were factor analyzed for a sample of two twenty-six eighth grade students. The first factor dominated the analysis with no other factor accounting for any substantial variance. Tables are presented and implications discussed. (JKS)

The accuracy of the varimax and promax methods of rotation of axes in reproducing known factor matrices was examined. It was found that only when all tests are univocal, or nearly so, could one be reasonably confident that an obtained factor matrix faithfully reproduces a contrived matrix. (Author/JKS)

A general linear model framework is used to suggest that structure coefficients ought to be interpreted in structural equation modeling confirmatory factor analysis (CFA) studies in which factors are correlated. Two heuristic data sets make the discussion concrete, and two additional studies illustrate the benefits of CFA structure coefficients.…

Presents a construction method for all factors that satisfy the assumptions of the model for factor analysis, including partially determined factors where certain error variances are zero. Illustrates that variable elimination can have a large effect on the seriousness of factor indeterminacy. (SLD)

Provides example applications of constrained principal component analysis (CPCA) that illustrate the method on a variety of contexts common to psychological research. Two new analyses, decompositions into finer components and fitting higher order structures, are presented, followed by an illustration of CPCA on contingency tables and the CPCA of…

Third step in development of perceptual inventory of factors associated with marijuana use involved administering inventory to 60 parents who were members of community anti-drug group. Factor analysis revealed 5-factor solution that used all 34 items. Scales were labeled Parental Limitations, Societal Issues, Inherent Predispositions,…

Properties of dichotomous Guttman-scalable items are described. Both the elements and eigenvalues of the Pearson correlation matrix of such items can be expressed as simple functions of the number of items if the score distribution is uniform and there is an equal number of items at each difficulty level. (SLD)

A method of assessing goodness-of-fit for a single factor model is presented. Indices of fit sensitive to the way that correlation matrices are generated are derived from the factor analysis literature. It is proposed that the cumulative distribution function be evaluated for other values of "p" and "m." (TJH)

A cross-validation method is described for selecting the significant components from a principal components analysis, and properties of the method are discussed. Parallels are drawn with other related methods in covariance structure modeling, and some comparisons among methods are illustrated with two data sets previously analyzed. (SLD)