A Bayesian Method for Model Optimization in Structural Equation Models with Mixed Continuous and Ordered Categorical Data

In this paper, a Bayesian criterion-based method called the Lv measure, as well as its calibration distribution, is introduced and applied to model optimization of structural equation models with mixed continuous and categorical data. A simulation study is presented to illustrate the satisfactory performance of the Lv measure in model optimization.