Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data

ArXi:2605.06989v1 Announce Type: cross 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.