The purpose of this paper is to demonstrate the use of the general linear model (GLM) in problems with repeated measures on a dependent variable. Such problems include pretest-posttest designs, multitrial designs, and groups by trials designs. For each of these designs, a GLM analysis is demonstrated wherein full models are formed and restrictions…

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…

Several procedures proposed in the literature for the analysis of growth curves are reviewed. Particular attention is given to the current issues in this area to guide practitioners in the selection of the most appropriate methodology. (Author)

The mini-computer is found to be a viable alternative to large computer bio-medical information processing. (Author/RS)

A method for computation of dominance relations and for construction of their corresponding hierarchical structures is presented. The link between dominance and variance allows integration of the mathematical theory of information with least squares statistical procedures without recourse to logarithmic transformations of the data. (Author/CTM)

Results of using multimethod factor analysis and exploratory factor analysis for the analysis of three multitrait-multimethod matrices are compared. Results suggest that the two methods can give quite different impressions of discriminant validity. In the examples considered, the former procedure tends to support discrimination while the latter…

This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…

Outlined is a model for transformation of one factor matrix to congruence with a second or target matrix in which the correlations among the transformed factors are constrained to certain pre-specified values. Procedures are developed for implementing the model, and are illustrated with example factor solutions. (Author/RC)

CLASSIFICATION OF DOCUMENTS INVOLVES THREE DISTINCT PROCESSES-- (1) DEFINING A STRUCTURE OF CATEGORIES, (2) DETERMINING A BASIS FOR A CLASSIFICATION DECISION, AND (3) CLASSIFYING DOCUMENTS INTO CATEGORIES. OF THE THREE COMPUTER TECHNIQUES ARE DISCUSSED FOR THE LAST TWO. A WORD SELECTION MEASURE IS USED TO DELETE THOSE TERMS IN THE DOCUMENT THAT…

New ways of using factor analysis in research designs are suggested in this paper that would allow research to move in new directions that are being suggested for educational technology. A brief simplified overview of factor-analytic techniques is given, followed by a description of some recent developments in factor-analytic techniques which make…

Multiple matrix sampling (MMS) procedures were utilized to determine the necessary parameters of a Pearson Type I curve. Empirical norms distributions were approximated by both the Type I model and the negative hypergeometric model. Four existing ITED norms distributions, two subtests and two grades, were approximated by the MMS procedures. Two…

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)

A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)

Criticizes a discussion of the reformation of post-TUCE learning equations by John Soper, which were presented in an earlier issue (see EJ 152 358). Claims that the author's manipulations from one equation to another essentially repackaged the same information. (Author/DB)

An asymptotic theory is developed for a new time series model introduced in TM 502 289. An algorithm for computing estimates of the parameters of this time series model is given, and it is shown that these estimators are asymptotically efficient in that they have the same asymptotic distribution as the maximum likelihood estimators. (Author/RC)