On-site Training

Structural Equation Modeling Using Stata

Description

This 2-day course covers the use of Stata for structural equation modeling (SEM). SEM is a class of statistical techniques for modeling relationships among variables, both observed and unobserved. SEM encompasses some familiar models such as linear regression, multivariate regression, and factor analysis and extends to a variety of more complicated models. The course will give an introduction to linear structural equation modeling. In addition, a number of models that fall within the SEM framework will be discussed with an emphasis on using Stata to fit each one. Stata allows for fitting structural equation models in two ways—by using the sem command syntax or using the graphical user interface to draw path diagrams. Examples will demonstrate both approaches.

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Course topics

• Overview of structural equation modeling
  • Model description
  • Process of fitting and evaluating structural equation models
  • Description of path diagrams
• Stata’s tools for SEM
  • Fitting models with the sem command
  • Building models using the GUI for SEM
  • Using the ssd commands to work with summary statistics
• Details on specific types of structural equation models
  • Models for observed variables
    • Linear regression
    • Correlation
    • Path analysis
    • Mediation analysis
  • Models with latent and observed variables
    • Confirmatory factor analysis
    • Full structural equation models
    • Latent growth curves
  • Multiple group models
• Testing and interpreting SEM results
• Standardized results
• Direct, indirect, and total effects
• Goodness-of-fit statistics
• Modification indices
• Score tests and Wald tests
• Tests for multiple group models

Prerequisite

Knowledge of basic statistical techniques such as correlation and linear regression.

Notes

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