Event Phone: 1-610-715-0115

Cancellation 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).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 5-Day Seminar Taught by Paul 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 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.

This 5-day seminar assumes no previous knowledge of SEM, and covers almost a full semester’s worth of material. It is designed to make you a knowledgeable, effective and confident user of methods for structural equation modeling. Each day will include 1 to 2 hours of supervised, practical exercises that will help you achieve mastery of these methods.

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

• 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.

How This Seminar Differs From Paul Allison’s 2-Day seminar “Introduction To Structural Equation Modeling”

This course includes all the material in the 2-day seminar, but in more detail, especially regarding models for categorical data. It also covers many other topics such as missing data, bootstrapping, formative indicators, interactions, and longitudinal data analysis. Lastly, much more time is devoted to exercises.