Psychological theories often produce hypotheses that pertain to individual differences in within‐person variability. To empirically test the predictions entailed by such hypotheses with longitudinal data, researchers often use multilevel approaches that allow them to model between‐person differences in the mean level of a certain variable and the residual within‐person variance. Currently, these approaches can be applied only when the data stem from a single variable. However, it is common practice in psychology to assess not just a single measure but rather several measures of a construct. In this paper we describe a model in which we combine the single‐indicator model with confirmatory factor analysis. The new model allows individual differences in latent mean‐level factors and latent within‐person variability factors to be estimated. Furthermore, we show how the model's parameters can be estimated with a maximum likelihood estimator, and we illustrate the approach using an example that involves intensive longitudinal data.

中文翻译：

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对潜在的人内变异的个体间差异建模：验证性因子水平变异模型

心理学理论通常会产生与人内可变性的个体差异有关的假设。为了用纵向数据对此类假设所包含的预测进行实证检验，研究人员经常使用多层次方法，使他们能够对某个变量的平均水平的人与人之间的差异和人内剩余的差异进行建模。目前，只有当数据来自单个变量时才能应用这些方法。然而，心理学中的常见做法不仅是评估一个指标，而是评估多个指标。构造的措施。在本文中，我们描述了一个模型，其中我们将单指标模型与验证性因素分析相结合。新模型允许估计潜在平均水平因素的个体差异和潜在的人内变异因素。此外，我们展示了如何使用最大似然估计器来估计模型的参数，并使用一个涉及密集纵向数据的示例来说明该方法。