Tackling Longitudinal Round-Robin Data: A Social Relations Growth Model
Tackling Longitudinal Round-Robin Data: A Social Relations Growth Model
复制标题
处理纵向循环数据：社会关系增长模型
作者：
S. Nestler;K. Geukes;R. Hutteman;M. Back
社会关系模型（SRM）通常用于分析群体中出现的人际判断和行为。 SRM 的开发仅用于横截面数据。在这里，我们介绍 SRM 对纵向数据的扩展。社会关系增长模型代表一个人对另一个人的重复 SRM 判断作为时间的函数。我们展示了如何使用限制最大似然估计模型的参数，以及如何计算协变量对个体间和夫妻间生长变异性的影响。提供一个示例来说明建议的方法。我们还提出了一项小型模拟研究的结果，显示了社会关系增长模型对于纵向 SRM 数据分析的适用性。
The social relations model (SRM) is commonly used in the analysis of interpersonal judgments and behaviors that arise in groups. The SRM was developed only for use with cross-sectional data. Here, we introduce an extension of the SRM to longitudinal data. The social relations growth model represents a person’s repeated SRM judgments of another person as a function of time. We show how the model’s parameters can be estimated using restricted maximum likelihood, and how the effects of covariates on interindividual and interdyad variability in growth can be computed. An example is presented to illustrate the suggested approach. We also present the results of a small simulation study showing the suitability of the social relations growth model for the analysis of longitudinal SRM data.
DOI：
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发表时间：
2015-10
期刊：
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影响因子：
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作者：
Douglas M. Bates;M. Maechler;Ben Bolker;Steven C. Walker
通讯作者：
Douglas M. Bates;M. Maechler;Ben Bolker;Steven C. Walker