ABSTRACT
This chapter focuses on the measurement model portion of latent variable structural equation modeling, more generally known as confirmatory factor analysis. At its most basic level, factor analysis is a reduction technique, a method of reducing many measures into fewer measures. The methodology works by placing scales or items that correlate highly with each other on one factor, while placing items that correlate at a low level with each other on different factors. With exploratory factor analysis, one analyzes a set of items or scales that presumably measures a smaller set of abilities, traits, or constructs. The development of factor analysis is inexorably linked with development of theories of intelligence and intelligence tests. Psychometric researchers are often also interested in understanding which of the subtests are most highly related to the global general intelligence factor.
