In this week’s episode Patrick and Greg discuss alternative methods for latent variable scaling, a topic about which we are often taught don’t make no nevermind but in actually can potentially make great nevermind. Along the way they also discuss favorite mathematicians, speed squares, drill bits, the quarter pounder, barley corns, butts and hogsheads, one Helen versus one Herbert, microcenturies, parlor tricks, being overserved, the Great Gonzo, but wait…there’s less, get on with it, and hiding the body.
Related Episodes
- S5E06: Advanced Factor Structures
- S4E10: Test Driving Model Identification
- S3E18: Aunt Roz’s Guide to Latent Means Models
- S2E21: Yes, Virginia…There ARE Latent Variables
Suggested Readings
Bollen, K. A., Lilly, A. G., & Luo, L. (2024). Selecting scaling indicators in structural equation models (SEMs). Psychological Methods, 29(5), 868–889.
De Pijper, W. M., & Saris, W. E. (1982). The effect of identification restrictions on the test of statistics in latent variable models. In K. G. Joreskog & H. Wold (Eds.), Systems under indirect observation, Part I (pp. 175-182). Amsterdam: North Holland.
Gonzalez, R., & Griffin, D. (2001). Testing parameters in structural equation modeling: every “one” matters. Psychological Methods, 6(3), 258-269.
Kang, Y., & Hancock, G. R. (2017). The effect of scale referent on tests of mean structure parameters. Journal of Experimental Education, 85(3), 376–388.
Klopp, E., & Klößner, S. (2021). The impact of scaling methods on the properties and interpretation of parameter estimates in structural equation models with latent variables. Structural Equation Modeling: A Multidisciplinary Journal, 28(2), 182-206.
Little, T. D., Slegers, D. W., & Card, N. A. (2006). A non-arbitrary method of identifying and scaling latent variables in SEM and MACS models. Structural equation modeling, 13(1), 59-72.
Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525–543.
Millsap, R. E. (2001). When trivial constraints are not trivial: The choice of uniqueness constraints in confirmatory factor analysis. Structural Equation Modeling, 8, 1–17