Structural Equation Modeling

This course covers fundamental knowledge for structural equation modeling (SEM). SEM is the statistical technique used to analyze relationships between latent variables.

Note

The articles written in English have blue links or blue table cells. The articles written in Thai have red links or red table cells.

Fall 2023 (Intro to Structural Equation Modeling; Undergraduate, CU)

Lectures Materials Assignments
Matrix Algebra
Confirmatory Factor Analysis (Part 1): Basic, Maximum Likelihood, Scaling, Standardized Parameters, Identification
Confirmatory Factor Analysis (Part 2): Model fit evaluation, Model Comparison, Mean Structure
Confirmatory Factor Analysis (Part 3): Equality Constraints, Additional Parameters, Factor Scores, Reliability
Structural Equation Modeling
Confirmatory Factor Analysis (Part 4): Hiearachical Model, Bifactor Model, Ordered Indicators
Parceling
Assumptions
Sample Size Planning

Class Notes

Structural model and report your result. Presentation. Assignment. Assignment Key. Script used for data generation.

Example codes for multiple-group invariance testing using lavaan. Easy way. Super thorough way.

Measurement invariance for categorical indicators Link.

Chi-square difference test for MLR estimator. Excel.