This basic and brief introduction to SEMs takes up several topics: The form and specification of observed-variable SEMs; instrumental-variables (IV) estimation; determining whether or not an SEM, once specified, can be estimated (the "identification problem"); estimation of observed-variable SEMs by IV, two-stage least-squares, and full-information maximum-likelihood; general structural-equation models with latent variables, measurement errors, and multiple indicators. The sem package in R will be used to estimate structural-equation models.
A sound background in single-equation regression models is assumed as is familiarity with basic statistical ideas, such as the method of maximum likelihood.
I also assume a basic knowledge of the R statistical computing environment. In addition to many books on R, there is a free introductory manual distributed with the software, as well as a variety of free contributed documentation.
Please make sure that R and the sem package are installed on your computer prior to the workshop.
K. A. Bollen, "Latent Variables in Psychology and the Social Sciences", Annual Review of Psychology, 2002, 53: 605-634, provides a good brief overview of latent-variable models; although it is now a bit dated, my favourite book-length treatment of SEMs remains K. A. Bollen, Structural Equations with Latent Variables (Wiley, 1989).
Cost: McMaster, $30; Non-McMaster academic, $55, non-academic, $100.
For further information: contact John Fox, jfox@mcmaster.ca.
To register: contact Danielle Stayzer, stayzer@mcmaster.ca, 905-525-9140x24484.
Last Modified: 2013-11-06 by John Fox <jfox AT mcmaster.ca>