A method is presented of calculating correlation matrices using single subscript rather than double subscript notation. This saves time and space, and permits the calculation of larger matrices in the space available. (Author)

The program can compute a great number of different correlation and other statistical measures. The user is free to select among the measures and also among the variables that are read by the program. When a particular set of variables has been treated in the prescribed way, a new set may follow together with new measure definitions. (Author)

A computer program which creates and stores a cumulative item covariance matrix upon each administration of an instrument is described. Use of this program would facilitate keeping a constant log on reliability in situations in which the test is administered to different groups over a period of time. (Author/JKS)

The program presented computes a chi-square statistic for testing pattern hypotheses on correlation matrices. The statistic is based on a multivariate generalization of the Fisher r-to-z transformation. This statistic has small sample performance which is superior to an analogous likelihood ratio statistic obtained via the analysis of covariance…

Part and bi-partial canonical correlations were developed by extending the definitions of part and bi-partial correlation to sets of variates. These coefficients may be used to help researchers explore relationships which exist among several sets of normally distributed variates. (Author)

A Computer program written in FORTRAN IV is presented which will create a population of desired size with marginally normal score vectors manifesting any desired centroid and covariance matrix. Uses and documentation are provided. (Author)

A general purpose computer program for the calculation of a matrix of tetrachoric correlations is described. This program was developed for use in adaptive (and other) testing research for examining the unidimensionality assumption in latent trait theory, in conjunction with available factor analysis programs. Several other potential applications,…

In some correlational studies it is not reasonable to assume that bivariate observations are uncorrelated. An example would be a configural analysis in which two individuals are correlated across several variables (e.g., Q-technique). The present study was a Monte Carlo investigation of the robustness of techniques used in judging the magnitude of…

The results of an algorithm which is designed to take a set of commonality coefficients, either real or manipulated, and, if possible, produce one or more sets of regressor correlations that are consistent with them are examined. A number of different ways of resolving the higher order commonality values into their lower orders were tried and the…

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…

Commonality analysis is an attempt to understand the relative predictive power of the regressor variables, both individually and in combination. The squared multiple correlation is broken up into elements assigned to each individual regressor and to each possible combination of regressors. The elements have the property that the appropriate sums…

INTERTAIL, the computer program which implements an approach to tailored testing outlined by Cliff (1975), was examined with errorless data in several Monte Carlo studies. Three replications of each cell of a 3 x 3 table with 10, 20 and 40 items and persons were analyzed. Mean rank correlation coefficients between the true order, specified by…

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…

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)