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Structural Equation Modeling

Event Details

Structural Equation Modeling

Time: July 11, 2016 at 9am to July 15, 2016 at 5pm
Location: The Gleacher Center at The University of Chicago Booth School of Business
Street: 450 North Cityfront Plaza Drive
City/Town: Chicago, IL
Website or Map: http://[email protected]
Phone: 610-642-1941
Event Type: training, seminar
Organized By: Statistical Horizons LLC
Latest Activity: Mar 7, 2016

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Event Description

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 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 exercis

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