Date(s) - 08/11/2020 - 08/14/2020
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This seminar will be hosted by Statistical Horizons.
Structural Equation Modeling I, Taught by Dr. Paul Allison
August 11th through August 14th (remote)
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
- 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 four days. This is an introductory course, and no previous knowledge of SEM is presumed.
The cost of attendance is $795.