Factor Analysis and Principal Components Analysis

This chapter provides a brief introduction to Factor Analysis and its “relatives,” including Exploratory Factor Analysis (EFA), Principal Components Analysis (PCA), and Confirmatory Factor Analysis (CFA) . The chapter helps the reader distinguish between these different methods used to help investigators decide how to represent a large number of relationships among normally distributed or scale variables in a simpler (more parsimonious) way. The chapter guides the reader to conduct EFA and PCA , both of which can be conducted using SPSS. If one has stronger, specific ideas about underlying constructs and how items should be related to them, CFA , in which one tests such specific models, should be used. EFA and CFA can help assess the level of construct (factorial) validity of a questionnaire purported to measure certain underlying (latent) constructs. Unfortunately, CFA requires Amos, so demonstration of this analysis is not provided, but the reader is guided as to when this analysis would be appropriate and desirable.