Introductory and Intermediate Structural Equation Modeling

This workshop deals with introductory and intermediate aspects of the increasingly popular structural equation modeling (SEM) methodology in the behavioral, educational, social, business, marketing and biomedical disciplines, and serves also as an introduction to the more comprehensive latent variable modeling (LVM) methodology of growing interest in these and related sciences.  The workshop begins with a coherent introduction to the basics of the methodology, including model identification issues, implied covariance and mean structure, parameter estimation, (robust) maximum likelihood estimation and (asymptotically) distribution-free estimation, as well as model fit evaluation.  Longitudinal data analysis is subsequently focused on, being concerned with fitting unconditional and subsequently conditional (covariate-based) models to data from repeated measure studies.  A discussion of analysis of data from nationally representative studies using complex designs follows then.  Throughout the workshop, multiple uses of numerical data and examples are made and the popular latent variable modeling program Mplus is employed.  The workshop is geared toward graduate students and faculty from the social, behavioral, biomedical and business disciplines.