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Bayesian analysis of two-level nonlinear structural equation models with continuous and polytomous data.

Xin-Yuan Song·Sik-Yum Lee
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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.

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Bayes TheoremHumansModels, PsychologicalNonlinear DynamicsJournal ArticleResearch Support, Non-U.S. Gov't

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Xin-Yuan Song, Sik-Yum Lee. 2004. Bayesian analysis of two-level nonlinear structural equation models with continuous and polytomous data.. https://doi.org/10.1348/000711004849259

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