Structural Equation Modeling
May 13-17, 2019
Chapel Hill, North Carolina
Instructors: Dan Bauer and Patrick Curran
Software Demonstrations: Mplus, R and Stata
Register for the Workshop
Structural Equation Modeling is a five-day workshop focused on the application and interpretation of statistical models that are designed for the analysis of multivariate data with latent variables. Although the traditional multiple regression model is a powerful analytical tool within the social sciences, this is also highly restrictive in a variety of ways. Not only are all variables assumed to have no measurement error, but it is also limited to a single dependent variable with unidirectional effects. The structural equation model (SEM) generalizes multiple regression to include multiple dependent variables, reciprocal effects, indirect effects, and the estimation and removal of measurement error through the inclusion of latent variables. The SEM is a general framework that allows for the empirical testing of research hypotheses in ways not otherwise possible. In this workshop we provide a comprehensive exploration of the SEM with topics ranging from introductory to advanced, as described in detail below.