Data reduction techniques seek to combine variables that account for patterns of variation in observed dependent variables in such a way that a simpler model is available for analysis. Factor analysis is a data reduction technique that attempts to model or explain a set of variables in terms of their associations. To understand why this technique…

The use of the 2 x 2 matrix in qualitative data analysis and theory generation is discussed, embracing the perspective that the objective of qualitative research in general and the analysis of qualitative data in particular is the development of theory. A 2 x 2 matrix is considered to be a tabular representation of the relationship of two…

This paper discusses the issue of multiple testing and overall Type I error rates in contexts other than multiple comparisons of means. It demonstrates, using a 5 x 5 correlation matrix, the application of 5 recently developed modified Bonferroni procedures developed by the following authors: (1) Y. Hochberg (1988); (2) B. S. Holland and M. D.…

The Galois-lattice is a graphic method for representing all possible developmental phases to reach a given total knowledge via different partial knowledge structures. Algorithms are proposed for incorporating statistical analysis into the Galois-lattice method. A comparison to the Rasch model and application for educational research are given. (BS)

Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)

The general transformation approach to time series analysis is extended to the analysis of multiple unit data by the development of a patterned transformation matrix. The procedure includes alternatives for special cases and requires only minor revisions in existing computer software. (SLD)

Tau, Lambda, and Kappa are measures developed for the analysis of discrete multivariate data of the type represented by stimulus response confusion matrices. The accuracy with which they may be estimated from small sample confusion matrices is investigated by Monte Carlo methods. (Author/LMO)

The first part of this four-part dissertation reviews conceptual and operational approaches to human communication systems. A new conceptual model for studying communication, General Algorithm for Studying Structuring in Complex Systems (GASSICS), is developed in the second part, and an operational method for applying GASSICS is presented in part…

Since computer programs have been available for estimating and testing linear causal models, these models have been used increasingly in the behavioral sciences. This paper discusses the problem that very different causal structures may fit the same set of data equally well. (Author/LMO)

Simplicity and flexibility of the full rank linear model motivated this paper which introduces researchers to the theory necessary to understand the model and apply the theory in the analysis of some standard fixed effects experimental designs. The theory and examples should help researchers use the model as an experimental tool and a model for…

Three methods of estimating a model of school effects are compared: ordinary least squares; an approach based on the analysis of covariance; and, a residualized input-output approach. Results are presented using a matrix algebra formulation, and advantages of the first two methods are considered. (Author/GK)

This paper illustrates the transformation of a raw data matrix into a matrix of associations, and then into a factor matrix. Factor analysis attempts to distill the most important relationships among a set of variables, thereby permitting some theoretical simplification. In this heuristic data, a correlation matrix was derived to display…

Several regression methods were examined within the framework of weighted structural regression (WSR), comparing their regression weight stability and score estimation accuracy in the presence of outlier contamination. The methods compared are: (1) ordinary least squares; (2) WSR ridge regression; (3) minimum risk regression; (4) minimum risk 2;…

A Monte Carlo study of five indices of dimensionality of binary items used a computer model that allowed sampling of both items and people. Five parameters were systematically varied in a factorial design: (1) number of common factors from one to five; (2) number of items, including 20, 30, 40, and 60; (3) sample sizes of 125 and 500; (4) nearly…

One of the most frequently used research methods in education and psychology involves repeated observations on the same individuals. When sample sizes are relatively small and a multivariate analysis lacks power, there are currently two analytical options in testing time effects. One is to assume a time series structure to these observations, and…