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…

In Bayesian structural equation modeling (BSEM), prior settings may affect model fit, parameter estimation, and model comparison. This simulation study was to investigate how the priors impact evaluation of relative fit across competing models. The design factors for data generation included sample sizes, factor structures, data distributions, and…

Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…