Model comparison of nonlinear structural equation models with fixed covariates

被引:55
|
作者
Lee, SY [1 ]
Song, XY
机构
[1] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
[2] Zhongshan Univ, Guangzhou, Peoples R China
关键词
nonlinear structural equation model; model comparison; Bayes factor; path sampling; Gibbs sampler; Metropolis-Hastings algorithm; sensitivity;
D O I
10.1007/BF02296651
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Recently, it has been recognized that the commonly used linear I structural equation model is inadequate to deal with some complicated substantive theory. A new nonlinear structural equation model with fixed covariates is proposed in this article. A procedure, which utilizes the powerful path sampling for computing the Bayes factor, is developed for model comparison. In the implementation, the required random observations are simulated via a hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm. It is shown that the proposed procedure is efficient and flexible; and it produces Bayesian estimates of the parameters, latent variables, and their highest posterior density intervals as by-products. Empirical performances of the proposed procedure such as sensitivity to prior inputs are illustrated by a simulation study and a real example.
引用
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页码:27 / 47
页数:21
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