An Introduction to Structural Equation Modeling for Medical Decision Making Research

Course Description and Objectives:

We present an overview of basic SEM principles, common nomenclature, diagrams, a tiny bit of algebra, and how to conduct SEM analyses with many relevant illustrative examples for medical decision-makers. We will introduce short course participants to some widely used SEM and related techniques for research such as factor analysis, mediation/moderation analysis, measurement equivalence testing, latent growth curve modeling, mixture modeling and partial least squares-SEM.

Finally, we will present analyses of real-world examples using SEM software. In this course, you will: 

  • Enrich your way of thinking about medical decision-making problems

  • Learn fundamental concepts underpinning structural equation models

  • Understand advantages of SEM over traditional statistical modeling

  • Gain knowledge of resources and techniques for causal modeling

  • Be able to interpret results of advanced causal modeling techniques

  • Be able to use results for guiding future theorization of mediation process

  • Be introduced to software for implementing SEM analyses

Whether you want to know how to critique a SEM article, use SEM in your research, or engage a few SEM researchers in some feisty methods discussions, sign up! We'd love to visit with you and share our expertise. In addition to our numerous collective peer-reviewed contributions to SEM and medical decision-making literatures, Drs. Gunzler, Perzynski, and Carle recently published "Structural Equation Modeling for Health and Medicine," a book written specifically for multidisciplinary researchers in medical settings who seek to understand and apply SEM in their work.

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