Statistical analysis of nonlinear structural equation models with continuous and polytomous data
Statistical analysis of nonlinear structural equation models with continuous and polytomous data
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DOI：
10.1348/000711000159303
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发表时间：
2000-11-01
影响因子：
2.6
通讯作者：
Zhu, HT
中科院分区：
文献类型：
--
作者：
Lee, SY;Zhu, HT
本文分析了一类具有混合连续变量和多变量的一般非线性结构方程模型。提出了一种贝叶斯方法，同时估计阈值，结构参数和潜变量。为了解决后验分析中的计算困难，混合马尔可夫链蒙特卡罗方法，结合吉布斯采样器和Metropolis-Hasting算法来产生贝叶斯解。统计推断，其中包括估计的参数和标准误差，残差和离群值分析，以及拟合优度统计检验假设的模型，进行了讨论。通过仿真研究和真实的例子说明了所提出的方法。
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.