AN INTRODUCTION TO STRUCTURAL EQUATION MODELING WITH THE sem PACKAGE FOR R

John Fox

Department of Sociology

McMaster University

 

 

 

Short URL: http://tinyurl.com/mac-sem

November 22, 2013, 9:00 AM - 6:00 PM

Location: McMaster University, DeGroote School of Business, Room A102

 

Aims of the Workshop

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.

Background

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.

Resources

Additional Reading

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>