Latent Variable Models in Clinical Psychology

Most of what clinical psychology concerns itself with is directly unobservable. Concepts like neuroticism and depression, but also learning and development, represent dispositions, states, or processes that must be inferred and cannot (currently) be directly measured. Latent variable modeling, as a statistical framework, encompasses a range of techniques that involve estimating the presence and effect of unobserved variables from observed data. This chapter provides a non-technical overview of latent variable modeling in clinical psychology. Dimensional latent variable models are emphasized, although categorical and hybrid models are touched on briefly. Challenges with specific models, such as the bifactor model are discussed. Examples draw from the psychopathology literature.