用典型点分析识别问卷中最具代表性的选项组合，提升对分类数据的理解。
Archetypal cases for questionnaires with nominal multiple choice questions
- 基于实际样本提取典型案例，用于描述问卷中的极端模式
- 在德国信贷数据集上验证，比传统方法更清晰揭示数据结构
- 适合研究分类题项的问卷分析，尤其关注典型回答模式
典型点分析是一种探索性工具，将一组观测值解释为纯（极端）模式的凸组合。当这些模式对应样本中的实际观测时，称为典型点。本文首次将典型点分析应用于分类型数据，专门用于从具有单一答案的名义多选题问卷中识别典型案例。该方法可增强对名义数据集的理解，类似于其在多元变量中的应用。我们将其与典型分析和概率典型分析进行比较，并通过真实案例——德国信贷数据集——展示了该方法的优势。
原文摘要 · Abstract (English)
Archetypal analysis serves as an exploratory tool that interprets a collection of observations as convex combinations of pure (extreme) patterns. When these patterns correspond to actual observations within the sample, they are termed archetypoids. For the first time, we propose applying archetypoid analysis to nominal observations, specifically for identifying archetypal cases from questionnaires featuring nominal multiple-choice questions with a single possible answer. This approach can enhance our understanding of a nominal data set, similar to its application in multivariate contexts. We compare this methodology with the use of archetype analysis and probabilistic archetypal analysis and demonstrate the benefits of this methodology using a real-world example: the German credit dataset.
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