##
Introduction to Structural-Equation Models

Structural equation models (SEMs) represent a
general approach to the statistical examination of
theoretical models fit to empirical data.
SEMs with latent variables embody simultaneous
equations with multiple exogenous and endogenous
variables (path analysis), along with measurement
error models (confirmatory factor analysis). Thus
SEMs are the synthesis of methods developed in
econometrics and psychometrics. This course
provides an introduction to the theory, and
empirical applications of SEMs within the "LISREL"
framework.

The course will examine the five steps that
characterize most applications of SEMs:

- model specification
- identification
- estimation
- assessment of model fit
- model respecification

The course will also address estimation problems
(improper solutions), and the problems involved in
the analysis of non-normal. The concept of
equivalent models will also be discussed.

The course will be of interest to those who plan to
utilize the general structural equation model with
latent variables or its specializations.

Familiarity with elementary matrix algebra will be
useful, though not essential, for understanding
LISREL syntax.