This is an updated version of the Structural Equation Modeling (PSYC 520T) I taught at California State University, Fullerton in the Spring of 2008 that was inspired by Fred Bryant's Structural Equation Modeling course (PSYC 525) at Loyola University Chicago in the spring of 2001. This time, I'm using lavaan in R rather than LISREL and I've swapped Kline and Bollen for which is the required and which is the recommended text. It's also influenced by excellent "Mini Lectures" from Matthew Hesson-McInnis's Covariance Structure Modeling (PSY 445) course at Illinois State University from the Spring of 2025. All the mistakes are mine.
Texts
Required
Bollen, K. A. (1989). Structural Equations with Latent Variables. Wiley.
Recommended
Beaujean, A, A. (2014). Latent Variable Modeling Using R: A Step-by-Step Guide. Routledge.
Bollen, K. A. (2026). Elements of Structural Equation Models (SEMs). Cambridge University Press.
Other Required Readings
Tanaka, J. (1993). Multifaceted conceptions of fit in structural equation models. In Bollen, K. A., & Long, J. S., Eds. Testing Structural Equation Models (pp. 10-39). Sage. (pdf)
Tabachnick, B. G., & Fidell, L. S. (2019). Chapter 13: Principal Components and Factor Analysis. In Using Multivariate Statistics, 7th Ed. Pearson. (pdf)
Tabachnick, B. G., & Fidell, L. S. (2019). Appendix A: A Skimpy Introduction to Matrix Algebra. In Using Multivariate Statistics, 7th Ed. Pearson. (pdf)
Some Pages with Links to Data Sources
ICPSR (Inter-University Consortium on Political and Social Research)
FIU (Florida International University) List of Public Use Datasets
Daily Materials
Markdown files are .RMD files (they may refer to images, so modification may be necessary)
Rendered files are .HTML files. Google won't display them, but they will display if you download them and open them.
Occasionally, I use SPSS datafiles; they are the .SAV files. I also occasionally simply have R code; those codes exist in .R files.
Week 1 Day 1
Week 1 Day 2
Week 2 Day 1
Week 2 Day 2
Week 3 Day 1
Week 3 Day 2
Week 4 Day 1
Week 4 Day 2
Week 5 Day 1
Sample Code Revision from Class
Week 5 Day 2
Week 6 Day 1
Files Mentioned in Recording
Measurement Invariance
Summed Scores vs. Using Loadings
Example Invariance Article
Week 6 Day 2
Week 7 Day 1
Week 7 Day 2
Week 8 Day 1
Review Day
Week 8 Day 2
Midterm Examination
Week 9 Day 1
Spring Break
Week 9 Day 2
Spring Break
Week 10 Day 1
Week 10 Day 2
Week 11 Day 1 (out of town, in lieu of class)
Sewall Wright Guinea Pig Article
Week 11 Day 2
Week 12 Day 1
Week 12 Day 2
Week 13 Day 1
Week 13 Day 2
Week 14 Day 1
Week 14 Day 2
Week 15 Day 1
Week 15 Day 2
Week 16 Day 1
Final Presentations
Week 16 Day 2
Drop In Zoom to Go Over Final Paper / Presentation Feedback
Homework
Homework #1 (Rendered, Key, Rendered Key)
Homework #2 (Rendered, Data File, Key, Rendered Key)
Homework #3 (Rendered, Data File, Key, Rendered Key)
Homework #4 (Rendered, Key, Rendered Key)
Midterm Exam
Fit Statistic Articles for Presentations
Maydeu-Olivares, Ximenez, & Revuelta (2024) GFI
Pavlov, Maydeu-Olivares, and Shi (2021) SRMR
Notes on the Steiger and Lind (1980) Handout on RMSEA
McNeish & Wolf (2023) Dynamic fit indices
Applied Article Presentations
Principal Components Analysis: Soto, C. J., & John, O. P. (2017). The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. Journal of Personality and Social Psychology, 13(1), 117-143. http://dx.doi.org/10.1037/pspp0000096 (pdf, .RMD)
Path Analysis: Wójcik, M., Neckar, J., & Niedźwieńska, A. (2022). Predictors of everyday prospective memory performance: A superiority in the execution of event-based tasks over time-based tasks reverses in real-life situations. Journal of Applied Research in Memory and Cognition, 11(2), 245–257. https://doi.org/10.1037/h0101872 (pdf, .RMD)
Path Analysis: Boateng (2025). Immigrants and the dying American dream: Longitudinal examiantion of the relationship between perceived discrimination and the future success of immigrants. Race and Justice, 0(0). https://doi.org/10.1177/21533687251391688. (pdf, .RMD)
Confirmatory Factor Analysis: Rossen, E., Kranzler, J. H., & Algina, J. (2008). Confirmatory factor analysis of the Mayer–Salovey–Caruso Emotional Intelligence Test V 2.0 (MSCEIT). Personality and Individual Differences, 44(5), 1258-1269. https://doi.org/10.1016/j.paid.2007.11.020 (pdf, .RMD)
Confirmatory Factor Analysis: Lövdén, M. (2003). The episodic memory and inhibition accounts of age-related increases in false memories: A consistency check. Journal of Memory and Language, 49(2), 268–283. https://doi.org/10.1016/S0749-596X(03)00069-X (pdf,.RMD)
Confirmatory Factor Analysis: Schaufeli, W.B., Salanova, M., González-Romá, V. & Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. Journal of Happiness Studies 3, 71–92. https://doi.org/10.1023/A:1015630930326. (pdf,.RMD)
Latent Variable Path Model: Arata, S., Masaki, Sugiuchi, Yazawa, R., Funatsu, H., & Kawakubo, S. (2025). Effects of perceived office environment on the subjective well-being of workers: Insights from a structural equation modeling analysis. Building and Environment, 27(Part B), 112180. https://doi.org/10.1016/j.buildenv.2024.112180 (pdf, .RMD)
Latent Variable Path Model: Barrick, M. R., Stewart, G. L., & Piotrowski, M. (2002). Personality and job performance: Test of the mediating effects of motivation among sales representatives. Journal of Applied Psychology, 87(1), 43–51. https://doi.org/10.1037/0021-9010.87.1.43. (pdf, .RMD)
Some Publication on Principal Components and Factor Analysis I've Found Particularly Useful
Tabachnick & Fidell on Reporting EFA/PCA
Bryant, F. B., & Yarnold, P. (1995)
Fabrigar, Wegener, MacCallum, & Strahan (1999)
Revelle's "Psychometric Theory" Chapter 6
Some Useful References on Writing Up Structural Equation Modeling Results
Quantfish Statistics Reporting Checklist (2026)
Raykov. Tomer, & Nesselroade (1991)
Structural Equation Modeling Listserv
LISTSERV - SEMNET Archives - LISTSERV.UA.EDU