Group scholars often describe or conceptualize groups as having characteristics similar to those of individuals. For example, groups can be thought of as motivated or satisfied in degree. Describing groups in such terms assumes that members possess similar levels of the characteristic in question and that latent group-level processes influence convergence on that characteristic. The latent group model (LGM) offers conceptual and statistical means for assessing the structure of latent, group-level factors based on the convergence of variables measured at the individual level. This paper outlines the conceptual issues related to the LGM and offers a detailed example using interaction data from 4-person groups for estimating the model in SAS—SPSS, Mplus, and R syntax are provided in the appendixes. Applications and extensions of the LGM are discussed.

中文翻译：

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潜在群模型的估计与应用。

群体学者经常将群体描述或概念化为具有与个体相似的特征。例如，群体可以被认为是有动机的或在程度上感到满意的。用这样的术语描述群体假设成员拥有所讨论特征的相似水平，并且潜在的群体水平过程会影响该特征的收敛。潜在群体模型 (LGM) 提供了概念和统计手段，用于根据在个体层面测量的变量的收敛性来评估潜在的群体层面因素的结构。本文概述了与 LGM 相关的概念问题，并提供了使用来自 4 人组的交互数据来估计 SAS 模型的详细示例——附录中提供了 SPSS、Mplus 和 R 语法。讨论了 LGM 的应用和扩展。