Introduction to Structural Equation Modeling

A 2-day seminar taught by Paul D. Allison, Ph.D.

Read reviews of this seminar


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 is 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 and behavioral sciences.

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

  • Test the implications of causal theories.
  • 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).
  • Adjust for measurement error in predictor variables.
  • Estimate and compare models across multiple groups of individuals.
  • Represent causal theories with rigorous diagrams.
  • Investigate the properties of multiple-item scales.

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 the opportunity to learn the basics of SEM from a master teacher, Professor Paul D. Allison, in just two days.


COMPUTING

The empirical examples and exercises in this course will emphasize Mplus, but equivalent code will be presented for SAS, Stata and lavaan (a new package for R). 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 required, you are encouraged to bring your own laptop (loaded with SAS, Stata, Mplus or lavaan) and do the optional exercises.


WHO SHOULD ATTEND?

This course is designed for researchers with a moderate 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. 


Location, format, materials.

The class will meet from 9 am to 4 pm each day with a 1-hour lunch break at Courtyard Fort Myers at Gulf Coast Town Center, 10050 Gulf Center Drive, Fort Myers, Florida 33913.

This hotel is part of a large shopping center with numerous stores, restaurants, and a movie theater. It’s 3 miles from the Fort Myers International Airport, and there is a complementary hotel shuttle to and from the airport. Although you can expect the weather to be comfortably warm (75 is the average high in January), this is definitely not a resort-type location. However, it’s about a half-hour drive to several attractive vacation areas, including Naples, Sanibel Island, and Fort Myers Beach.

The Fort Myers International Airport (RSW) is served by numerous airlines with direct flights to and from most major cities in the U.S. However, demand for seats in January is quite high, so be sure to make reservations at your earliest opportunity.

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. 


Registration and Lodging

The fee of $995 includes all course materials.  The early registration fee of $895 is available until December 27.

Refund Policy
If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50). 

Lodging Reservation Instructions

Three hotels are recommended: 

Please make your own reservations at the Courtyard or the Residence Inn. For the Hilton Garden, we have arranged a special rate of $159 per night. To get this rate, call 239-210-7205 during business hours and use group code “STAT.” The room block will expire when it is full or on Tuesday, December 27, 2016.

Please make sure to book your hotel as early as possible. 


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


Comments from Recent participants

“This course provided a terrific overview of SEM, building from foundational concepts of path analysis and measurement to a wide variety of useful techniques. I found the course to be a highly efficient and effective way to refresh (and refine) my knowledge of SEM. I now feel much more confident applying SEM in my own research.”
  Michael Broda, Virginia Commonwealth University

“Dr. Allison clearly has depth and breadth of knowledge of SEM. I have a better understanding of SEM, the use of MPlus and STATA, and the statistical theory behind SEM as a result of the course. It was especially helpful in learning code or Stata to run SEM analyses. Dr. Allison is a rock star statistician!”
  Julia Phillips, Cleveland State University

“This course provided excellent guidance for me as I conceptualized my dissertation analyses. I feel prepared to answer new research questions using rigorous methodological approaches.
  Carolyn Bates, Loyola University Chicago

“This course provided an excellent way to learn how to use SEM to answer a large variety of questions. I came to the course with little to no previous knowledge of SEM and am leaving feeling that I am capable of running SEM analyses on my own data. I found the exercises particularly useful for solidifying the lesson material. As someone without much coding experience, I found that the slides with the codes for the different programs were well explained and therefore, easy to follow. I would definitely recommend this course to someone looking to learn SEM.”
  Moriah Sokolowski, University of Western Ontario

“This was a fantastic course – Professor Allison was knowledgeable and extremely clear when discussing the concepts underlying SEM. He patiently answered questions, which helped our understanding. The exercises allowed us to practice using the various software packages.”
  Cynthia Wang, Oklahoma State University

“Traveling from Senegal to Chicago is a long way. The contents of this training together with the way it is taught fully match my expectations when registering for this training. Professor Allison is a great and tireless teacher. I do feel privileged and lucky to benefit from this SEM course and wish success to Statistical Horizons in its efforts to skill researchers.”
  Oswald Koussihouede, CONFEMEN

“It’s rare to find a short course at the right level and of the right depth for those new to a concept and those more experienced alike. This course was just that – palatable for someone new to SEM methods (like me) and with enough depth offered for more experienced in Stata. Dr. Allison is a savvy and experienced teacher with a great wealth of knowledge. 
  Lorraine Dean, Johns Hopkins Bloomberg School of Public Health

“Beautifully organized. I have taken two courses taught by Dr. Allison and I am always impressed by how easily he explains a lot of complex stat concepts. That tells me he is an excellent instructor from experience. Highly recommend!”
  SeungYong Han, Arizona State University

“This is a very practical course. There are lots of detailed examples with ample time given to specifics of program code, interpreting output and testing assumptions. The course is ideal for professionals who are not professional statisticians, but who nevertheless need and would benefit from a practical and detailed introduction to SEM.”
  Ian Lyons, The University of Western Ontario

“I had a semester-long course in SEM eight years ago but have not used SEM a great deal since then. This was a great course that provided more up-to-date thinking on methods and analysis as well as an understanding of current software. I would highly recommend this course as an introduction to SEM or as a comprehensive refresher.”
  Cindy Guthrie, Bucknell University 

“I have been trying to teach myself SEM for years, but failed to find an effective and efficient way to do it. Finally your seminar helped me to connect all the SEM dots in my mind and even much more! 
  Yue Yin, UIC College of Education