This workshop deals with introductory and intermediate aspects of the increasingly popular methodology of structural equation modeling (SEM) in the behavioral, educational, social, business, marketing, and biomedical disciplines. 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 specifically with fitting unconditional and conditional (covariate-based) models to data from repeated measures studies. A discussion of analysis of data from nationally representative studies using complex designs then follows. Throughout the workshop, multiple uses of numerical data and examples are utilized and the popular latent variable modeling program Mplus is employed (as well as passing references to Stata, version 12, are made where appropriate). The workshop is geared toward graduate students and faculty from the social, behavioral, biomedical and business disciplines.