Structural Equation Modeling
May 11-15, 2020
Online Webinar via Zoom
Instructors: Dan Bauer and Patrick Curran
Software Demonstrations: Mplus, R, and Stata
Note that this workshop will be held the same week as our Network Analysis workshop
Register for the Workshop
*To be eligible, participant must be actively enrolled in a degree-granting graduate or professional school program at the time of the workshop. Post-doctoral fellows are not eligible for the student rate.
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.
Relative to our free 3-day Introduction to SEM, this class provides:
- Greater depth on shared topics
- Coverage of advanced topics such as multiple groups modeling, growth curve models and SEMs with categorical indicators
- Demonstrations in a broader range of software programs, including Mplus and Stata as well as R
- Greater interactivity with instructors, with the opportunity to ask individualize questions during the lecture