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PubMed · 11109705

Statistical analysis of nonlinear structural equation models with continuous and polytomous data.

S Y Lee·H T Zhu
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Abstract

A general nonlinear structural equation model with mixed continuous and polytomous variables is analysed. A Bayesian approach is proposed to estimate simultaneously the thresholds, the structural parameters and the latent variables. To solve the computational difficulties involved in the posterior analysis, a hybrid Markov chain Monte Carlo method that combines the Gibbs sampler and the Metropolis-Hasting algorithm is implemented to produce the Bayesian solution. Statistical inferences, which involve estimation of parameters and their standard errors, residuals and outliers analyses, and goodness-of-fit statistics for testing the posited model, are discussed. The proposed procedure is illustrated by a simulation study and a real example.

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

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S Y Lee, H T Zhu. 2000. Statistical analysis of nonlinear structural equation models with continuous and polytomous data.. https://doi.org/10.1348/000711000159303

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