Examining individual differences in how interaction behaviors change over time: A dyadic multinomial logistic growth modeling approach.
Examining individual differences in how interaction behaviors change over time: A dyadic multinomial logistic growth modeling approach.
复制标题
检查交互行为如何随时间变化的个体差异：二元多项逻辑增长建模方法。
DOI：
10.1037/met0000605
复制
发表时间：
2023
影响因子：
7
通讯作者：
Ram, Nilam
中科院分区：
文献类型：
--
作者：
Brinberg, Miriam;Bodie, Graham D.;Solomon, Denise H.;Jones, Susanne M.;Ram, Nilam
一些理论观点认为，二元体验的区别在于互动过程中出现的行为变化模式。对于沿着连续维度的变化研究，很好地阐述了检查行为随时间变化的方法。然而，用于绘制个人使用特定的、分类定义的行为的增加和减少的扩展很少被调用。贝叶斯框架有助于制定和估计必要的模型，这一框架的更大可及性正在开辟新的可能性。这篇文章提供了一个入门如何多项式逻辑增长模型可以用来检查二分体之间的差异，在二分体内的行为变化的过程中的相互作用。我们描述和说明这些模型是如何实现的贝叶斯框架中使用的数据，从支持陌生人之间的对话（N= 118二人组）检查（RQ 1）如何六种类型的听众和听众的行为变化的支持对话展开和（RQ 2）如何听众的谈话前的痛苦缓和的会话行为的变化。本书最后给出了一系列注释：（a）建模选择的含义，（B）建模非线性变化的灵活性，（c）指定变化轨迹如何以及为什么不同的理论的必要性，以及（d）多项式逻辑增长模型如何帮助完善当前关于二元相互作用的理论。（PsycInfo数据库记录（c）2023阿帕，保留所有权利）
Several theoretical perspectives suggest that dyadic experiences are distinguished by patterns of behavioral change that emerge during interactions. Methods for examining change in behavior over time are well elaborated for the study of change along continuous dimensions. Extensions for charting increases and decreases in individuals’ use of specific, categorically defined behaviors, however, are rarely invoked. Greater accessibility of Bayesian frameworks that facilitate formulation and estimation of the requisite models is opening new possibilities. This article provides a primer on how multinomial logistic growth models can be used to examine between-dyad differences in within-dyad behavioral change over the course of an interaction. We describe and illustrate how these models are implemented in the Bayesian framework using data from support conversations between strangers (N= 118 dyads) to examine (RQ1) how six types of listeners’ and disclosers’ behaviors change as support conversations unfold and (RQ2) how the disclosers’ preconversation distress moderates the change in conversation behaviors. The primer concludes with a series of notes on (a) implications of modeling choices,(b) flexibility in modeling nonlinear change,(c) necessity for theory that specifies how and why change trajectories differ, and (d) how multinomial logistic growth models can help refine current theory about dyadic interaction.(PsycInfo Database Record (c) 2023 APA, all rights reserved)