Introduction to Structural Equation Modeling (SEM)

Introduction to Structural Equation Modeling

taught by Randall Schumacker

Aim of Course:

Structural Equation Modeling (SEM) is a general statistical modeling technique to establish relationships among variables. A key feature of SEM is that observed variables are understood to represent a small number of "latent constructs" that cannot be directly measured, only inferred from the observed measured variables. This online course covers the theory of SEM, and includes practical work with computer software and real data. It covers the key concepts in SEM - at the conclusion of the course students will be able to specify different forms of models, using observed, latent, dependent and independent variables. Student will be able to conduct confirmatory factor analysis, and diagram SEM models.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1: Preliminaries

  • LISREL software installation
  • Data entry and Data Edit issues
  • Correlation and Covariance Data Files

WEEK 2: Modeling

  • SEM Basics
  • Regression models
  • Diagramming Models
  • Path Analysis Models

WEEK 3: Measurement Models

  • Exploratory vs. Confirmatory factor analysis
  • Latent Variables
  • CFA models

WEEK 4: Developing Structural Equation Models

  • Combining Path and Factor Models
  • 5 Basic SEM steps
    • Model Specification
    • Model Identification
    • Model Estimation
    • Model Testing
    • Model Modification
  • Amos Audio/Video Presentation


Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

In addition to assigned readings, this course also has supplemental readings available online, and an exam.

Introduction to Structural Equation Modeling (SEM)

Who Should Take This Course:
Researches and analysts who want to go beyond simple models and incorporate multi-directionality, multiple causes and latent variables.
Participants should have some familiarity with statistical modeling (e.g. regression) and the basics of educational measurement and assessment.
Organization of the Course:
Options for Credit and Recognition:
Course Text:
All necessary materials are provided in the course.  For those wishing more detail and a ready reference the recommended course text is A Beginner's Guide to Structural Equation Modeling, 4th edition, published Dec 2015, by Randall E. Schumacker and Richard Lomax.

The course will provide illustrations in LISREL, a programming environment. You can download a free student version of LISREL from the textbook website. The Introductory guide and user's manual are also available here. TA's can provide LISREL support if needed.

Course staff will not be available to illustrate or help with examples other than those included in the course. Students are encouraged to visit each software website to obtain the latest student versions of the software. Some, but not all software can be obtained on vendor websites.

MAC users note: LISREL software is not available for Macintosh. Mac end users run the Windows editions of the software products using Virtual PC or VM on Power PC Macs (G series) or the Windows OS on Intel-based Macs.



May 10, 2019 to June 07, 2019 November 01, 2019 to November 29, 2019 May 15, 2020 to June 12, 2020 October 30, 2020 to November 27, 2020

Introduction to Structural Equation Modeling (SEM)


May 10, 2019 to June 07, 2019 November 01, 2019 to November 29, 2019 May 15, 2020 to June 12, 2020 October 30, 2020 to November 27, 2020

Course Fee: $589

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