The analysis of longitudinal data collected from nonexchangeable dyads presents a challenge for applied researchers for various reasons. This article introduces the dyadic curve-of-factors model (D–COFM), which extends the curve-of-factors model (COFM) proposed by McArdle (1988) for use with nonexchangeable dyadic data. The D–COFM overcomes problems with modeling composite scores across time and instead permits examination of the growth in latent constructs over time. The D–COFM also appropriately models the interdependency among nonexchangeable dyads. Different parameterizations of the D–COFM are illustrated and discussed using a real data set to aid applied researchers when analyzing dyadic longitudinal data.

中文翻译：

---

二元因子曲线模型：纵向不可交换二元数据模型的介绍和说明

由于各种原因，对从不可交换的二元组收集的纵向数据的分析对应用研究人员提出了挑战。本文介绍了因子曲线模型 (D-COFM)，它扩展了 McArdle (1988) 提出的因子曲线模型 (COFM)，用于不可交换的二元数据。D-COFM 克服了跨时间建模综合分数的问题，而是允许检查潜在构造随时间的增长。D-COFM 还适当地模拟了不可交换的二元组之间的相互依赖性。使用真实数据集说明和讨论了 D-COFM 的不同参数化，以帮助应用研究人员分析二元纵向数据。