Newly available data streams from experience sampling studies and social media are providing new opportunities to study individuals’ dyadic relations. The “one-with-many” (OWM) model (Kenny et al., 2006; Kenny & Winquist, 2001) was specifically constructed for and is used to examine features of multiple dyadic relationships that one set of focal persons (e.g., therapists, physicians) has with others (e.g., multiple clients, multiple patients). Originally, the OWM model was constructed for and applied to cross-sectional data. However, the model can be extended to accommodate and may be particularly useful for the analysis of intensive repeated measures data now being obtained through experience sampling and social media. This article (a) provides a practical tutorial on fitting the OWM model, (b) describes how the OWM model is extended for analysis of repeated measures data, and (c) illustrates application of the OWM model using reports about interpersonal behavior and benefits individuals experienced in 64,111 social interactions during 9 weeks of study (N = 150). Our presentation highlights the utility of the OWM model for examining interpersonal processes in everyday life. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

中文翻译：

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二元分析和互惠一对多模型：利用密集的纵向数据扩展人际交往过程的研究。

来自经验抽样研究和社交媒体的新可用数据流为研究个人的二元关系提供了新的机会。“一对多” (OWM) 模型 (Kenny et al., 2006; Kenny & Winquist, 2001) 专门用于检查一组焦点人物（例如治疗师）的多重二元关系的特征，医生）与其他人（例如，多个客户，多个患者）。最初，OWM 模型是为横截面数据构建并应用于横截面数据的。然而，该模型可以扩展以适应并可能对分析现在通过经验抽样和社交媒体获得的密集重复测量数据特别有用。本文（一）提供了拟合OWM模型的实用教程，N = 150)。我们的演讲强调了 OWM 模型在检查日常生活中的人际交往过程中的实用性。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）