ABSTRACT
This chapter will focus in more detail on the measurement model of latent variable struc tural 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. Because one primary reason items correlate highly with one another is that they measure the same construct, factor analysis provides insights as to the common constructs measured by a set of scales or items. Because it helps answer questions about the constructs measured by a set of items, factor analysis is a major method of estab lishing the internal validity of tests, questionnaires, and other measurements. You can also think of factor analysis as a method of establishing convergent and divergent validity: items that measure the same thing form a factor (converge), whereas items that measure different constructs form a separate factor (diverge).
