S6E07 Structural After Measurement and the Muffin of Truth

S6E07_graphic

In this week’s episode Greg and Patrick talk about the advantages of recent structural after measurement work, allowing us to break apart traditional structural equation models to analyze the measurement and structural portions separately. Along the way they also discuss the baseball playoffs, fire pit face plants, the gluten cabinet, pumpkin inadequacy, a soupçon of ginger, free range muffins, fancy pants souffles, drunken whac-a-mole, flexing lats, and blue on black.

Related Episodes

  • S5E15: Classical Test Theory (in bed)
  • S1E22: Factor Analysis: The Good, The Bad, & The Ugly
  • S1E13: How Do I Get Scale Scores? Weight, Weight… Don’t Tell Me!
  • S1E12: Measurement (Non)Invariance: Can We Ever Fail to Not Incorrectly Reject It?
  • S1E09: Grumpy Old Man & Village Idiot Argue About Reliability

Recommended Readings

Cole, D. A., & Preacher, K. J. (2014). Manifest variable path analysis: Potentially serious and misleading consequences due to uncorrected measurement error. Psychological Methods, 19 (2), 300–315.

Croon, M. (2002). Using predicted latent scores in general latent structure models. In G. Marcoulides & I. Moustaki (Eds.), Latent variable and latent structure models (pp. 195–223). Lawrence Erlbaum.

Devlieger, I., & Rosseel, Y. (2017). Factor score path analysis: An alternative for SEM? Methodology, 13, 31–38.

Dhaene, S., & Rosseel, Y. (2023). An Evaluation of Non-Iterative Estimators in the Structural after Measurement (SAM) Approach to Structural Equation Modeling (SEM). Structural Equation Modeling: A Multidisciplinary Journal30(6), 926-940.

Hancock, G. R., & Mueller, R. O. (2011). The reliability paradox in assessing structural relations within covariance structure models. Educational and Psychological Measurement, 71(2), 306–324.

Robitzsch, A. (2022). Comparing the robustness of the structural after measurement (SAM) approach to structural equation modeling (SEM) against local model misspecifications with alternative estimation approaches. Stats5(3), 631-672.

Rosseel, Y., & Loh, W. W. (2022). A structural after measurement approach to structural equation modeling. Psychological Methods.

Skrondal, A., & Laake, P. (2001). Regression among factor scores. Psychometrika, 66 (4), 563–575.

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