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 LISREL 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


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:

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Digital Badge - Courses evaluated by the American Council on Education have a digital badge available for successful completion of the course.  
  5. Other options - Specializations, INFORMS CAP recognition, and academic (college) credit are available for some courses
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 15, 2020 to June 12, 2020 October 30, 2020 to November 27, 2020

Introduction to Structural Equation Modeling (SEM)


May 15, 2020 to June 12, 2020 October 30, 2020 to November 27, 2020

Course Fee: $589

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