Structural Equation Models PHL 2011

Philadelphia, Pennsylvania
Thursday, June 09, 2011
Structural Equation Models PHL 2011
Thursday, June 09, 2011 9:00 AM -
Friday, June 10, 2011 4:00 PM (Eastern Time)

Temple University Center City
1515 Market St.
Philadelphia, Pennsylvania 19103
United States

Map and Directions

Introduction to Structural Equation Models

A 2-Day Seminar

Taught by Paul D. Allison, Ph.D.


Structural Equation Modeling (SEM) is a statistical methodology that is widely used by researchers in the social, behavioral and educational sciences.  First introduced in the 1970s, SEM was a marriage of psychometrics and econometrics.  On the psychometric side, SEM allows for latent variables with multiple indicators. On the econometric side, SEM allows for multiple equations, possibly with feedback loops.  In today's SEM software, the models are so general that they encompass most of the statistical methods that are currently used in the social sciences.  

Here Are a Few Things You Can Do With Structural Equation Models

    • Test complex causal theories with multiple pathways.
    • Estimate simultaneous equations with reciprocal effects.
    • Incorporate latent variables with multiple indicators.
    • Investigate mediation and moderation in a systematic way.
    • Handle missing data by maximum likelihood (better than multiple imputation).
    • Analyze longitudinal data. 
    • Estimate fixed and random effects models in a comprehensive framework.
    • Adjust for measurement error in predictor variables.

Because SEM is such a complex and wide-ranging methodology, learning how to use it can take a substantial investment of time and effort. Now, you have a unique opportunity to learn the basics of SEM from a master teacher, Professor Paul D. Allison, in just two days.

Who Should Attend

This course is designed for researchers with a modest statistical background who want to apply SEM methods in their own research projects. No previous background in SEM is necessary.  But participants should have a good working knowledge of basic principles of statistical inference (e.g., standard errors, hypothesis tests, confidence intervals), and should also have a good understanding of the basic theory and practice of linear regression.


While there are several computer packages designed for SEM, Mplus will be used for all the empirical examples and exercises in this course. Mplus is one of the best SEM packages because of its superior capabilities for missing data, multi-level modeling, and ordinal and categorical data.  Although not essential, participants are welcome to bring their own laptop computers to the class.

Schedule and materials

The class will meet from 9 to 4 each day with a 1-hour lunch break.
Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking.

Course outline

1.  Introduction to SEM
2.  Path analysis
3.  Direct and indirect effects
4.  Identification problem in nonrecursive models
5.  Reliability and validity
6.  Multiple indicators of latent variables
7.  Exploratory factor analysis
8.  Confirmatory factor analysis
9.  Goodness of fit measures
10. Structural relations among latent variables
11. Alternative estimation methods.
12. Multiple group analysis
13. Models for ordinal and nominal data

Registration and lodging

The fee of $795 includes all course materials. If you register no later than May 6, the fee is reduced to $695.  The course will be held at Temple University Center City, just across from the Philadelphia City Hall.

Cancellations received two weeks before the course begins are fully refundable (minus a $50 processing fee if you paid by credit card).

Participants must make their own arrangements for lodging. A block of rooms has been reserved at the Club Quarters Hotel, a 5-minute walk from the course locations.  For more information, click on the Lodging tab at the top of this page.

Comments by Recent Participants in Paul Allison’s Short Courses

"This was one of the best stats courses I've every taken, the other being Allison's Missing Data course. I understood concepts that I didn't grasp through my previous stats courses. The information is very clearly explained, and practical examples used to illustrate concepts. The rationale behind why things are done in a certain way is clearly explained."

  Margaret Hsieh, University of Pittsburgh Medical Center

"Thorough, clearly presented treatment of a complex topic."

  Palmer Bessey, Weil Cornell Medical College

“This is an outstanding environment for researchers who use statistics, but are not statisticians, to develop and augment their knowledge and improve their work. Allison does a great job relating the material to everything from education to business.”

  Jacob Gross, Indiana University

For information on other courses, go to




Contact Information

Payment Instructions

  • All major credit cards are accepted. The fee of $795 includes all course materials. If you register on or before May 6, the fee is discounted to $695.

    If you are paying by check, make the check out to Statistical Horizons and send to

    Statistical Horizons
    530 New Gulph Rd.
    Haverford, PA  19041

    If you want to pay by purchase order, please email a copy of the purchase order to, or fax it to 419-818-1220.

    Our Tax ID number is 26-4576270.

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