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Latent variable models with ordinal categorical covariates

机译:具有序数分类协变量的潜在变量模型

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摘要

We propose a general latent variable model for multivariate ordinal categorical variables, in which both the responses and the covariates are ordinal, to assess the effect of the covariates on the responses and to model the covari-ance structure of the response variables. A fully Bayesian approach is employed to analyze the model. The Gibbs sam-pler is used to simulate the joint posterior distribution of the latent variables and the parameters, and the parame-ter expansion and reparameterization techniques are used to speed up the convergence procedure. The proposed model and method are demonstrated by simulation studies and a real data example.
机译:我们为多元有序分类变量提出了一个通用的潜在变量模型,其中响应和协变量都是有序的,以评估协变量对响应的影响并为响应变量的协方差结构建模。采用完全贝叶斯方法来分析模型。 Gibbs sam-pler用于模拟潜在变量和参数的联合后验分布,并且参数扩展和重新参数化技术用于加快收敛过程。通过仿真研究和一个真实的数据实例证明了所提出的模型和方法。

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