Bayesian Approach to Structural Equation Models. For Ordered Categorical and Dichotomous Data

      Аннотация: This book represents a general idea on using Bayesian analysis in structural equation models for two different types of data "ordered categorical and dichotomous". This book focuses on Convergence of the Gibbs Sampling Algorithm using "BGR DIAGNOSTIC". The ordered categorical and dichotomous data are handled using censoring and truncation methods. The choice between the models depends on the parameter estimation results and the goodness-of-fit statistics, Deviance Information Criterion (DIC).

Ключевые слова: Bayesian approach, Structural equation models, Ordered categorical data, dichotomous data