Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum likelihood and least squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood ratio…

Many researchers recognize that factors can be rotated obliquely, yielding factors that are correlated with each other. However, not as many researchers realize that this interfactor correlation matrix can then also be factor analyzed. This "higher-order" factor analysis has many useful applications and, in fact, some researchers suggest…

Attributional style as it has been operationalized in the Attributional Style Questionnaire (ASQ) was critically assessed. A sample of 538 senior high school and college students completed the ASQ. The resulting ASQ data were then intercorrelated, factor analyzed, and compared to hypothesized matrices for all items, good outcome items, and bad…

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,…

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…

A multitrait-multimethod matrix containing two methods of measuring 12 personality traits was analyzed and confirmatory factor analysis was applied to the data. Although unexplained variance remained, method factors and a general personality factor significantly improved the fit of a model containing only trait factors. (Author/RL)

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

The factor-referenced kits developed by the Educational Testing Service (ETS) are assessed. With support from the National Science Foundation, the researcher surveyed the total range of research done over the past 65 years on the identification of cognitive abilities, principally through factor analysis. From a corpus of an estimated 2,000 data…

An exploratory factor analysis is used in the study of institutional preferences in medical student admissions. Sources and mathematical derivations of 58 institutional variables are presented. Most of the measures describe attributes related to the admission process. The remainder were selected to represent other dimensions along which medical…

Procedures for simultaneous confirmatory factor analysis in several populations are useful in a variety of problems. This is demonstrated with examples involving missing data, comparison of part correlations between groups, testing the equality of regression weights between groups with multiple indicators of each variable, and the formulation of…

The use of indices and statistics based on nonlinear factor analysis (NLFA) has become increasingly popular as a means of assessing the dimensionality of an item response matrix. Although the indices and statistics currently available to the practitioner have been shown to be useful and accurate in many testing situations, few studies have…

The impact of the use of data arising from balanced incomplete block (BIB) spiralled designs on the chi-square goodness-of-fit test in factor analysis is considered. Data from BIB designs posses a unique pattern of missing data that can be characterized as missing completely at random (MCAR). Standard approaches to factor analyzing such data rest…

The Children's Interaction Matrix, Intermediate and Primary Forms, are designed to identify the preferred work and content styles of children in group situations. These factors aid the researcher, teacher, and counselor in understanding the individual's preferred mode of behavior in groups as well as indicating the students' reaction to group…

A Monte Carlo investigation of simplex fitting as a method of determining the dimensionality of binary data matrices was conducted. Examination of the fit of correlation matrices with a known factor structure to correlation matrices that represent the perfect simplex shows that simplex fitting is a feasible approach under some circumstances. (SLD)

An approach for multiple factor analysis of dichotomized variables is presented based on distribution of first and second order joint probabilities of binary scored items. The estimator is based on the generalized least squares principle. Standard errors and a test of the fit of the model is given. (Author/RC)