二元社会互动

D. Iacobucci, S. Wasserman
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引用次数: 37

摘要

Kraemer和Jacklin(1979)提出了一种分析单变量二元社会互动或关系数据的方法,Mendoza和Graziano(1982)将这种方法扩展到多变量关系。他们的方法基于方差分析型模型,该模型包含表征参与者和合作伙伴行为的参数,以及他们在每种关系中的相互作用。本文中介绍的技术通过认识到许多关系产生离散值数据,从而通过使用为分类数据设计的方法更好地建模,为社会互动的多变量分析提供了另一种方法。这种替代方法也更通用,因为它允许拟合更多类型的模型。我们将使用前面方法分析的相同数据进行说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dyadic Social Interactions
Kraemer and Jacklin (1979) proposed a method of analysis of univariate dyadic social interactions or relational data, and Mendoza and Graziano (1982) extended this method to multivariate relations. Their approach is based on an analysis-of- variance-type model that contains parameters characterizing the behavior of actors and partners and their interactions on each relation. The techniques presented in this article offer an alternative approach to the multivariate analysis of social interactions by realizing that many relations yield discrete-valued data and thus are better modeled by using methods designed for categorical data. This alternative approach is also more general because it allows more types of models to be fit. We illustrate, using the same data analyzed by the earlier methods.
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