Drawing upon recent developments in structural equation modeling, the current study presents an analytical framework for addressing research questions in which, rather than focusing on means, it is intraindividual (or intragroup) variability that is of direct research interest. Beyond merely serving as an alternative to existing multilevel modeling approaches, this framework allows for extensions to accommodate a variety of complex research scenarios by parameterizing variability as a latent variable that can in turn be embedded within a broader covariance and mean structure involving other observed and/or latent variables. The estimation procedures and parameter interpretation for the latent random variability models are discussed. The versatility of the proposed methods is demonstrated through four empirical examples. The Mplus, BUGS, and Stan model syntax for the illustrative examples are supplied to facilitate the application of the methods.

中文翻译：

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一种结构方程建模方法，用于将可变性建模为潜在变量。

借鉴结构方程建模的最新发展，当前的研究提出了一个分析框架，用于解决研究问题，而不是关注手段，而是直接研究兴趣的是个体内（或组内）变异性。除了作为现有多级建模方法的替代方案之外，该框架还允许扩展以通过将可变性参数化为潜在变量来适应各种复杂的研究场景，该潜在变量又可以嵌入到更广泛的协方差和均值结构中，涉及其他观察到的和/或潜在变量。讨论了潜在随机变异模型的估计程序和参数解释。通过四个经验示例证明了所提出方法的多功能性。Mplus、BUGS、