A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)

A method of assessing rater reliability via a design of overlapping rater teams is presented. Covariances or correlations of ratings can be analyzed with LISREL models. Models in which the rater reliabilities are congeneric, tau-equivalent, or parallel can be tested. Two examples based on essay ratings are presented. (TJH)

An equation derived by W. A. Nicewander and J. M. Price relating statistical power to reliability of dependent variable measures when true score regression is homogeneous across treatment conditions is enhanced through overcoming the problem of directly estimating the squared linear correlation between true scores for X and Y. (SLD)

A technique is presented to transform incomplete categorical data into complete data by imputing appropriate scores into missing cells. A solution of the optimization problem is suggested, and relevant psychometric theory is discussed. The average correlation should be at least 0.50 before the method becomes practical. (SLD)

The degree of agreement between two raters rating several objects for a single characteristic can be expressed through an association coefficient, such as the Pearson product-moment correlation. How to select an appropriate association coefficient, and the desirable properties and uses of a class of such coefficients--the Euclidean…

A brief overview is provided of the Conger-Lipshitz approach to estimating the reliability of a profile or test battery. A computational example from a recent study shows how canonical reliability can be obtained through existing statistical software. (SLD)

Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)

The use of complex value-added models that attempt to isolate the contributions of teachers or schools to student development is increasing. Several variations on these models are being applied in the research literature, and policy makers have expressed interest in using these models for evaluating teachers and schools. In this article, we…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…

Educational outcomes are affected by student level, classroom level, and school level characteristics. The fact that educational data are multilevel in nature poses serious analysis questions. Though strong arguments can be made for focusing on a single level of analysis, such studies have several basic limitations: the choice of analytic level…

This study compared three approaches to the two-factor experiment with repeated measures on one factor: (1) the conventional mixed model analysis of variance, (2) the Greenhouse-Geisser conservative analysis of variance, and (3) multivariate extensions of analysis of variance. Computer simulated data were used in a total of 96 sets of covariance…

This study involved an investigation of the use of Pearson r, tetrachoric r, phi, phi/phi maximum, and Kendall Tau-B coefficients as measures of association for the incomplete principal components analysis of simulated Likert scale attitudinal data, based on a known factor pattern and possessing different types of severe departures from normality.…

Three topics in factor analysis are covered: a) a reliability coefficient for assessing the quality of a maximum likelihood factor analysis, b) an application of three-mode factor analysis to serial learning data, showing variations in learning curves over stages of learning and individuals, and c) the use of personal probability functions to…

Guttman's "rank-reduction" theorem is employed to demonstrate how most of the algebra and computational work for standard correlational and analysis of variance methods can be examined within a single matrix system. Analyses of both correlational and experimental data are illustrated with an easy-to-use computer program. This application…