Structural equation modeling for those who think they don't care
We will discuss SEM (structural equation modeling), not from the perspective of the models for which it is most often used--measurement models, confirmatory factor analysis, and the like--but from the perspective of how it can extend other estimators. From a wide range of choices, we will focus on extensions of mixed models (random and fixed-effects regression). Extensions include conditional effects (not completely random), endogenous covariates, and others.
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