Description
At CenterStat, we have long been committed to providing broad access to high-quality training opportunities for students in the social, behavioral and health sciences. We are thus very excited to announce the return of our *free* workshop, Introduction to Structural Equation Modeling, 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 the linear regression model 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 introduction to SEM that includes path analysis, confirmatory factor analysis, and structural equation models with latent variable and which focuses on both establishing a conceptual understanding of the model and how it is applied in practice.
