• Corpus ID: 865255

Latent class models for clustering : a comparison with K-means

@inproceedings{Magidson2002LatentCM,
  title={Latent class models for clustering : a comparison with K-means},
  author={Jay Magidson and Jeroen K. Vermunt},
  year={2002}
}
Recent developments in latent class (LC) analysis and associated software to include continuous variables offer a model-based alternative to more traditional clustering approaches such as K-means. In this paper, the authors compare these two approaches using data simulated from a setting where true group membership is known. The authors choose a setting favourable to K-means by simulating data according to the assumptions made in both discriminant analysis (DISC) and K-means clustering. Since… 

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