The anatomy of models II: latent variables

Abstract

Concepts associated with latent variables What is a latent variable? As indicated in our overview of structural equation models at the beginning of Chapter 3, in addition to observed variables in structural equation models, another type of variable, referred to as a latent variable, is commonly included. There are a variety of ways latent variables can be defined. Strictly speaking, a latent variable is one that is hypothesized to exist, but that has not been measured directly. Bollen (2002) states that we can simply think of a latent variable as one that is unobserved. In spite of this simple definition, latent variables are typically used to represent concepts. However, there are many types of concept and not all of them correspond to latent variables. Further, the algorithms used to calculate latent variables define their quantitative properties, although how they are interpreted is a matter of theoretical consideration. Finally, latent variables are starting to be used in structural equation models for a wider variety of purposes, such as to represent parameters in latent growth modeling. Because latent variables are often used to represent abstractions, their meaning is not always immediately obvious. For this reason, I believe it will be best to rely on a variety of examples and a discussion of their properties to illustrate the roles latent variables can play in SEM.