ABSTRACT
In this chapter, the concept of confirmatory factor analysis is introduced along with how it is different from exploratory factor analysis. The fundamental basics of setting up a confirmatory factor analysis is discussed along with model fit indices. Factor loadings and squared multiple correlations are introduced and how it relates to convergent and discriminant validity. Techniques to address validity include average variance extract vs. shared variance and heterotrait-monotrait ratio of correlations.
The second half of the chapter focuses on more advanced topics as they relate to measurement models in SEM. Measurement model invariance testing is addressed, including full and partial metric invariance. Other topics such as common method bias, formative vs. reflective indicators, and second order constructs are discussed. Lastly, common error messages for CFA models in AMOS are introduced and remedies are suggested.
