Both common factor analysis and components analysis are useful techniques for reducing the number of variables in a data set or for identifying underlying covariance structures that exist among a set of variables. Although researchers have for some years debated the appropriateness of selecting one of these methods over the other, components…

Historically, most researchers conducting factor analysis have used exploratory methods. However, more recently, confirmatory factor analytic methods have been developed that can directly test theory either during factor rotation using "best fit" rotation methods or during factor extraction, as with the LISREL computer programs developed…

The purpose of the present study was to determine how two different data collection techniques would affect the Q-factors derived from several factor analytic procedures. Faculty members (N=146) from seven middle schools responded to 61 items taken from an instrument designed to measure aspects of an idealized middle school culture; the instrument…

This paper demonstrates how Q-methodology combines artistic and scientific procedures to allow social science researchers to develop and test theories about differences in persons. Q-methodology is based on factor analysis. In R-technique factor analysis, the most commonly used technique, variables define the columns and persons define the rows of…