title: Bayesian analysis of two-level nonlinear structural equation models with continuous and polytomous data.
abstract: Two-level structural equation models with mixed continuous and polytomous data and nonlinear structural equations at both the between-groups and within-groups levels are important but difficult to deal with. A Bayesian approach is developed for analysing this kind of model. A Markov chain Monte Carlo procedure based on the Gibbs sampler and the Metropolis-Hasting algorithm is proposed for producing joint Bayesian estimates of the thresholds, structural parameters and latent variables at both levels. Standard errors and highest posterior density intervals are also computed. A procedure for computing Bayes factor, based on the key idea of path sampling, is established for model comparison.
authors.affiliation: Department of Statistics, The Chinese University of Hong Kong.
authors.forename: Xin-Yuan
authors.initials: XY
authors.lastname: Song
authors.forename: Sik-Yum
authors.initials: SY
authors.lastname: Lee
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D008960:Models, Psychological; D017711:Nonlinear Dynamics