Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data
K-means clustering is widely used in psychological and psychometric research to identify profiles, subgroups, and potential typologies, yet its classical formulation does not test whether such groups exist as latent psychological categories. Instead, K-means partitions multidimensional space into regions around centroids, favoring compact, approximately spherical clusters defined by geometric distance. In this paper, we examine this limitation through a sequence of controlled simulated datasets. We then extend the analysis to the SMARVUS dataset, a large international psychometric dataset comprising survey responses from university students across 35 countries, to evaluate whether similar...
| Authors | Pedro Henrique Ramos Pinto, Maria Jullyanna Ferreira Marques, Luiz Carlos Serramo Lopez |
|---|---|
| Primary category | stat.AP |
| Published | 7 May 2026 |
| Last updated at source | 7 May 2026 |
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