SUBJECT

Title

Introduction to Practice of Structural Equation Modeling

Code

DPSY16-QNR-102

Type of instruction

practice

Level

Doctoral

Part of degree program
Credits

7

Recommended in

Semester 1-4

Typically offered in

Autumn/Spring semester

Course description

The goal is to introduce students to the practice of structural equation modeling (SEM) with examples. SEM is often used in latent variable modeling. After the discussion of basic concepts of SEM, we focus on confirmatory factor analysis, path analysis, structural regression analysis, and latent class analysis. We use Mplus programs: (1) Confirmatory factor analysis is appropriate when our goal is to confirm a measurement model or compare measurement
models. (2) Path analysis is a type of SEM when we use only observed variables in testing complex patterns of associations. (3) Structural regression analysis is a type of path analysis with latent variables. (4) Latent class analysis is used when the latent variable is categorical. (5) Introduction to “item response theory”, the basis of modern psychometry.

This is an interactive course in which the instructor and the students can work on real datasets, perform the analysis, and make conclusions.

Readings
  • Kline R. B. (2011). Principles and practice of structural equation modeling. New York: The Guilford Press 3rd Edition.
  • Brown, T.A. (2006). Confirmatory Factor Analysis for Applied Research. New York: The Guilford Press.
  • Geiser, C. (2012). Data Analysis with Mplus. New York: The Guilford Press.