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...
| Publicado en: | American Statistician Vol. 63; no. 1; pp. 81 - 92 |
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| Autores principales: | , , |
| Formato: | Product Evaluation |
| Publicado: |
American Statistical Association
February 2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=508041377&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 508041377 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: N pubinfo: dt: February 2009 vid: 63 iid: 1 pid: 543 pub: American Statistical Association artinfo: ui: 508041377 10.1198/tast.2009.0016 ppf: 81 ppct: 11 formats: tig: atl: Review of Three Latent Class Cluster Analysis Packages: Latent Gold, poLCA, and MCLUST. aug: au: 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 refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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