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A Spectral Clustering Approach to the Structure of Personality:Contrasting the FFM and HEXACO Models

机译:人格结构的谱聚类方法:对比FFm和HEXaCO模型

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摘要

Alternative analytic methods may help resolve the dimensionality of personality and the content of those dimensions. Here we tested the structure of personality using spectral clustering and conventional factor analysis. Study 1 analysed responses from 20,993 subjects taking the 300-item IPIP NEO personality questionnaire. For factor analysis, a five-factor solution recovered the FFM domains while the six-factor solution yielded only a small and hard to interpret sixth factor. By contrast, spectral clustering analysis yielded six-cluster solutions congruent with the HEXACO model. Study 2 analysed data from 1,128 subjects taking the 100-item HEXACO-PI-R. Unambiguous support was found for a six-cluster solution. The psychological content of the 6 clusters and their relationship to the FFM domains is discussed.
机译:替代分析方法可能有助于解决人格的维度和这些维度的内容。在这里,我们使用频谱聚类和常规因子分析测试了人格的结构。研究1分析了300993个IPIP NEO人格问卷对20993名受试者的回答。对于因子分析,五因子解决方案恢复了FFM域,而六因子解决方案仅产生了很小且难以解释的第六因子。相比之下,频谱聚类分析得出与HEXACO模型一致的六聚类解。研究2分析了100项HEXACO-PI-R中1,128名受试者的数据。找到了对六集群解决方案的明确支持。讨论了6个类群的心理内容及其与FFM域的关系。

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