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Latent Class Analysis Variable Selection1
We propose a method for selecting variables in latent class analysis, which is the most common model-based clustering method for discrete data. The method assesses a variable’s usefulness for clustering by comparing two models, given the clustering variables already selected. In one model the variab...
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| Hoofdauteurs: | , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2010
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2934856/ https://ncbi.nlm.nih.gov/pubmed/20827439 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10463-009-0258-9 |
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