Explicit formulas are derived for the asymptotic sampling variances and covariances of the maximum likelihood estimators for factor-analysis parameters in the special case where there is just one common factor. The effect of the number of variables on these variances and covariances is indicated. A formula is given showing to what extent the usual…

Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…

The jackknife by groups and modifications of the jackknife by groups are used to estimate standard errors of rotated factor loadings for selected populations in common factor model maximum likelihood factor analysis. Simulations are performed in which t-statistics based upon these jackknife estimates of the standard errors are computed.…

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)

This paper is concerned with the study of similarities and differences in factor structures between different groups. A common situation is when a battery of tests has been administered to samples of examinees from several populations. A very general model is presented, in which any parameter in the factor analysis models (factor loadings, factor…

This study of maximum likelihood confirmatory factor analysis found effects of practical significance due to sample size, the number of indicators per factor, and the number of factors for Joreskog and Sorbom's (1981) goodness-of-fit index (GFI), GFI adjusted for degrees of freedom, and the root mean square residual. (Author/BW)

This report gives some simple examples of stability for one factor and 2 x 2 factorial analysis of variance, reliability and correlations. The findings are very different: from superstability (no transformation whatsoever can change the result) to almost total instability. This is followed by a discussion of applications to multivariate analysis,…

The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model, and principal axes factor analyses were performed. (Author/LMO)

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)

This partially annotated bibliography of journal articles, dissertations, convention papers, research reports, and a few books and unpublished manuscripts provides a comprehensive coverage of work on latent trait theory and practice. Documents are arranged alphabetically by author. The period covered ranges from the early 1950's to the present.…