Seminar in Psychometrics

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The structural-after-measurement (SAM) approach to structural equation modeling

Date and time: March 5, 2022 (3:40 PM CET)
Place On Zoom and in K4 at MFF UK

Abstract. In structural equation modeling (SEM), the measurement and structural parts of the model are usually estimated simultaneously. In this presentation, I will revisit the long-standing idea that we should first estimate the measurement part, and then estimate the structural part. We call this the 'Structural-After-Measurement' (SAM) approach to SEM. I will describe a formal framework for the SAM approach under settings where the latent variables and their indicators are continuous. I will also discuss earlier SAM methods and establish how they are specific instances of the SAM framework. Simulation results will be presented showing several advantages of the SAM approach: 1) estimates exhibit smaller finite sample biases under correctly specified models, 2) estimation routines are less vulnerable to convergence issues in small samples, and 3) estimates are more robust against local model misspecifications. The SAM framework includes two-step corrected standard errors, and permits computing both local and global fit measures. Finally, for a large class of models, non-iterative estimators can be used in both stages.

Rosseel, Y. & Loh, W. W. (2021). A structural-after-measurement (SAM) approach to SEM. OSF preprint

Yves Rosseel,
Ghent University