Department of Methodology and Statistics, Leiden University, The Netherlands.
Department of Statistics, London School of Economics and Political Science, London, UK.
Br J Math Stat Psychol. 2021 May;74(2):340-362. doi: 10.1111/bmsp.12227. Epub 2020 Nov 16.
In this article we provide an overview of existing approaches for relating latent class membership to external variables of interest. We extend on the work of Nylund-Gibson et al. (Structural Equation Modeling: A Multidisciplinary Journal, 2019, 26, 967), who summarize models with distal outcomes by providing an overview of most recommended modeling options for models with covariates and larger models with multiple latent variables as well. We exemplify the modeling approaches using data from the General Social Survey for a model with a distal outcome where underlying model assumptions are violated, and a model with multiple latent variables. We discuss software availability and provide example syntax for the real data examples in Latent GOLD.
在本文中,我们提供了现有方法的概述,这些方法用于将潜在类别成员与感兴趣的外部变量联系起来。我们扩展了 Nylund-Gibson 等人的工作(结构方程建模:多学科杂志,2019 年,26 卷,967),他们通过提供带有协变量和多个潜在变量的较大模型的最推荐的建模选项概述,总结了具有远程结果的模型。我们使用一般社会调查的数据来说明模型的方法,其中存在潜在模型假设违反的远程结果模型,以及具有多个潜在变量的模型。我们讨论了软件的可用性,并为 Latent GOLD 中的实际数据示例提供了示例语法。