Sociology | Topics in Quantitative Sociology
S651 | 3673 | Long

S651 Topics in Quantitative Sociology   (3 CR)
Topic:  Structural Equation Modeling
3672 1:00P - 2:15P       TR   BH 316
S651 Lab
3673 4:00P - 6:00P       TR   BH 308
Scott Long
Office: BH 744

Structural equation modeling (SEM) is a general method for
analyzing the relationship among variables.  In its most complex
form, SEM allows you to have multiple equations with errors in
equations and errors of measurement for all the variables in the
model.  The course will approach this very general model by
progressing through a series of special cases that are quite
useful and powerful in and of themselves.  First, we will
consider simultaneous equations systems for multiple regression.
In this form of the model, all of the variables are measured
without error.  Next, we consider the case in which all variables
are measured with error, but that there is a structural
relationship among the variables.  This form of SEM is referred
to as confirmatory factor analysis.  The advantage of
confirmatory factors analysis compared to exploratory factor
analysis is considered.  Finally, we will consider the full model
in which simultaneous equation systems and measurement error are
combined.  Note that the SEM goes by various names, including
covariance structure analysis and LISREL modeling.

This is a graduate level class in applied statistics that assumes
familiarity with the linear regression model as taught in
Sociology 554.  Students will be required to write a substantive
paper using structural equation modeling, or a methodological
paper dealing with a problem in SEM.