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ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices

机译:ADPROCLUS:图形用户界面,用于通过可变数据矩阵将加性剖面聚类模型拟合到对象

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摘要

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin’s additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.
机译:在心理学的许多领域中,人们感兴趣的是揭示通过可变数据集生成对象的潜在结构机制。通常,基于理论或经验论据,可以预期这些基础机制暗示将对象分组为允许重叠的簇(即,一个对象可能属于多个簇)。在这种情况下,使用Mirkin的附加配置文件聚类模型分析数据可能是合适的。在此模型中:(1)每个对象可能不属于一个,几个或几个聚类;(2)每个聚类都有一个特定的变量配置文件;(3)可以通过添加来重建对象在变量上的得分有关对象所属的群集的特定于群集的变量概要文件。但是,到目前为止,还没有公开可用的软件程序来执行附加配置文件聚类分析。为此,在本文中,将介绍由图形用户界面操纵的ADPROCLUS程序。我们将通过症状数据矩阵对患者的分析进一步说明其用途。

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