Department of Psychology, Katholieke Universiteit Leuven, Leuven, Belgium.
Psychol Methods. 2011 Sep;16(3):361-71. doi: 10.1037/a0024446.
Profile data abound in a broad range of research settings. Often it is of considerable theoretical importance to address specific structural questions with regard to the major pattern as included in such data. A key challenge in this regard pertains to identifying which type of interaction (double ordinal, mixed ordinal/disordinal, double disordinal) most adequately fits the major pattern in a profile data set at hand. In the present article a novel methodology is proposed to deal with this challenge. This methodology is based on constrained and unconstrained versions of a recently introduced 2-mode clustering model, the real-valued hierarchical classes model. The methodology is illustrated using empirical Person × Situation profile data on altruism.
个人资料在广泛的研究环境中都有大量存在。通常,对于包含在这些数据中的主要模式,解决特定的结构问题具有相当大的理论重要性。在这方面的一个关键挑战是确定哪种类型的相互作用(双重有序、混合有序/无序、双重无序)最适合手头的个人资料数据集的主要模式。本文提出了一种新的方法来应对这一挑战。该方法基于最近引入的 2 模式聚类模型——实值层次类模型的约束和非约束版本。该方法使用利他主义的实证个人与情境资料进行了说明。