A Latent Variable Model for Ordinal Variables
A Latent Variable Model for Ordinal Variables
复制标题
序数变量的潜变量模型
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
I. Moustaki
中科院分区：
文献类型：
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作者：
I. Moustaki
讨论了用全信息极大似然法拟合一组有序观测变量的多维潜变量模型。该方法是对有序变量和具有一个有序因变量和观察到的所有解释变量的回归模型的一般模型的实现。本文还讨论了模型的估计、人在潜在维度上的评分以及模型的拟合优度。将该方法应用于一个关于技术态度的示例数据集。
A full-information maximum likelihood method for fitting a multidimensional latent variable model to a set of ordinal observed variables is discussed. This method is an implementation of a general class of models for ordinal variables, and for regression models with one ordinal dependent variable and all explanatory variables observed. Estimation of the model, scoring of persons on the latent dimensions, and the goodness-of-fit of the model are also discussed. The method is applied to an example dataset concerning attitudes toward technology.