Module 26: Structural Equation Modeling

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Structural equation modeling (SEM) is a versatile statistical modeling tool. Its estimation techniques, modeling capacities, and breadth of applications are expanding rapidly. This module introduces some common terminologies. General steps of SEM are discussed along with important considerations in each step. Simple examples are provided to illustrate some of the ideas for beginners. In addition, several popular specialized SEM software programs are briefly discussed with regard to their features and availability. The intent of this module is to focus on foundational issues to inform readers of the potentials as well as the limitations of SEM. Interested readers are encouraged to consult additional references for advanced model types and more application examples.

Keywords: estimation, factor, latent variable, measurement model, path model, structural equation modeling, SEM

Pui-Wa Lei

Professor of Education, Pennsylvania State University

Dr. Lei’s teaching and research interests are in the areas of advanced statistical methods and measurement theories. Her research has focused on applications of item response theory (IRT) and methodological issues of multivariate statistical analyses. Currently, she is studying issues related to applications of structural equation modeling (SEM), multilevel modeling, and IRT modeling.

Qiong Wu


Module 26: Introduction to Structural Equation Modeling: Issues and Practical Considerations
Open to download resource.
Open to download resource.