A Bayesian Approach for Multigroup Nonlinear Factor Analysis

The main purpose of this article is to develop a Bayesian approach for a general multigroup nonlinear factor analysis model. Joint Bayesian estimates of the factor scores and the structural parameters subjected to some constraints across different groups are obtained simultaneously. A hybrid algorithm that combines the Metropolis-Hastings algorithm and the Gibbs sampler is implemented to produce these joint Bayesian estimates. It is shown that...