ABSTRACT
With exploratory factor analysis, we deviated from concerning our analyses with procedures that have the examination of one or more a priori outcomes as their goal and branched into a procedure that allows exploration of data to reduce a large number of variables into identifiable clusters of variables to better understand the structure of the data. This chapter continues that tradition a bit with the treatment of confirmatory factor analysis-a tool often used as follow-up to EFA. In this chapter, we will also touch on path analysis. Path analysis and confirmatory factor analysis (CFA) both fall under the umbrella of structural equation modeling (SEM). Structural equation modeling is a collection of regression-based statistical procedures that allow the examination of relationships of observed as well as unobserved variables. For the purposes of this text, we will focus primarily on path analysis and CFA with a brief segue into SEM. Path analysis can be considered a special case of SEM with only observed variables, and confirmatory factor analysis can be considered a special case of SEM with measurement models only.
