Factor analysis is a statistical technique that is widely used in psychology and social sciences. Using computers and statistical packages, implementation of multivariate factor analysis and other multivariate methods becomes possible for researchers. Exploratory factor analysis and confirmatory factor analysis are applied in different studies;…

Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…

Agile methods and approaches such as eXtreme programming (XP) have become the norm for successful organizations not only in the software industry but also for businesses seeking to improve internal software processes. Pair programming in some form is touted as a major functionality and productivity improvement. However, numerous studies show that…

Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

Provided is a description of three methods for testing certain types of a priori hypotheses about differences among covariance matrices. Briefly outlined are procedures for using two computer programs, COFAMM and LISREL, for testing such hypotheses. Also provided are examples of application of the methods to a meaningful data set. (Author/BW)

Through a review of the literature, this paper explores the viability of the rotation of canonical correlation analysis results. The similarities and dissimilarities between factor analysis and canonical correlation analysis are examined. The logic supporting a preference for the rotation of structure coefficients as opposed to function…

A component analytic method for analyzing multivariate longitudinal data is presented that does not make strong assumptions about the structure of the data. Central to the method are the facts that components are derived as linear composites of the observed or manifest variables and that the components must provide an adequate representation of…