Review of Three Latent Class Cluster Analysis Packages: Latent Gold, poLCA, and MCLUST.

A review of three software packages that can be used to perform latent class cluster analysis—Latent Gold®, MCLUST, and poLCA—is presented. A single dataset is used, and each software package is applied to develop a latent class cluster analysis for the data, which allows for the comparison of the...

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Publicado en:American Statistician Vol. 63; no. 1; pp. 81 - 92
Autores principales: Haughton, Dominique, Legrand, Pascal, Woolford, Sam
Formato: Product Evaluation
Publicado: American Statistical Association February 2009
Acceso en línea:Ver este registro en EBSCOhost
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      pub: American Statistical Association
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        10.1198/tast.2009.0016
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        atl: Review of Three Latent Class Cluster Analysis Packages: Latent Gold, poLCA, and MCLUST.
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          Haughton, Dominique
          Legrand, Pascal
          Woolford, Sam
      su: Statistical software
      sug:
        subj: Statistical software
      keyword: Cluster analysis -- Computer programs -- Reviews
      ab: A review of three software packages that can be used to perform latent class cluster analysis—Latent Gold®, MCLUST, and poLCA—is presented. A single dataset is used, and each software package is applied to develop a latent class cluster analysis for the data, which allows for the comparison of the features and the resulting clusters from each software package. The strengths and weaknesses of each software package are discussed and compared in terms of usability, cost, data characteristics, and performance. Factors to consider when choosing a package are suggested.
      pubtype: Academic Journal
      doctype: Product Evaluation
      src: R
    language: English
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