Statistics IV Statistical Modeling

Catalog description

This course is a general treatment of a class of techniques that have come to be known as structural equation modeling procedures. Structural Equation Modeling (SEM) is a general class of multivariate modeling techniques that allows the estimation of relationships between latent (unobserved) variables. It is also a regression based technique that combines both confirmatory factor analysis and path analysis. The overall goal of this course is to provide students with the conceptual aspects, statistical underpinnings, and applications of this method. It is not meant to be a tutorial on how to use a specific software. The course is intended to be very applied in the sense of how to estimate models, evaluate them, revise them, and report the results. At the same time, the course will provide a rigorous treatment of the theory underlying SEM, including discussions of causality and inference, model assumptions and consequences of their violation, and limitations.