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Distinguishing Outcomes from Indicators via Bayesian Modeling
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Levy, Roy – AERA Online Paper Repository, 2017
A conceptual distinction is drawn between indicators, which serve to define latent variables, and outcomes, which do not. However, commonly used frequentist and Bayesian estimation procedures do not honor this distinction. They allow the outcomes to influence the latent variables and the measurement model parameters for the indicators, rendering…
Descriptors: Bayesian Statistics, Structural Equation Models, Sampling, Goodness of Fit