Nonlinear patterns of change arise frequently in the analysis of repeated measures from longitudinal studies in psychology. The main feature of nonlinear development is that change is more rapid in some periods than in others. There generally also are strong individual differences, so although there is a general similarity of patterns for different persons over time, individuals exhibit substantial heterogeneity in their particular response. To describe data of this kind, researchers have extended the random coefficient model to accommodate nonlinear trajectories of change. It can often produce a statistically satisfying account of subject-specific development. In this review we describe and illustrate the main ideas of the nonlinear random coefficient model with concrete examples.

中文翻译：

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使用随机系数模型分析非线性变化模式。

在对心理学纵向研究中的重复测量进行分析时，经常会出现非线性变化模式。非线性发展的主要特征是，某些时期的变化要比其他时期的变化更快。通常，个人差异也很大，因此，尽管随着时间的流逝，不同人的模式普遍相似，但个人的特定反应表现出很大的异质性。为了描述这种数据，研究人员扩展了随机系数模型，以适应非线性的变化轨迹。它通常可以得出特定学科发展的统计令人满意的记录。在这篇综述中，我们用具体的例子来描述和说明非线性随机系数模型的主要思想。