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  • 标题:Recovering a Basic Space from Issue Scales in R
  • 本地全文:下载
  • 作者:Keith T. Poole ; Jeffrey B. Lewis ; Howard Rosenthal
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2016
  • 卷号:69
  • 期号:1
  • 页码:1-21
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:basicspace is an R package that conducts Aldrich-McKelvey and Blackbox scaling to recover estimates of the underlying latent dimensions of issue scale data. We illustrate several applications of the package to survey data commonly used in the social sciences. Monte Carlo tests demonstrate that the procedure can recover latent dimensions and reproduce the matrix of responses at moderate levels of error and missing data.
  • 关键词:multivariate;R;scaling
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