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文章基本信息

  • 标题:The Impact of Equating on Detection of Treatment Effects
  • 本地全文:下载
  • 作者:Youn-Jeng Choi ; Seohyun Kim ; Allan S. Cohen
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2018
  • 卷号:17
  • 期号:2
  • 页码:22
  • 出版社:Wayne State University
  • 摘要:Equating makes it possible to compare performances on different forms of a test. Three different equating methods (baseline selection, subgroup, and subscore equating) using common-item item response theory equating were examined for their impact on detection of treatment effects in multilevel models.
  • 关键词:Common-item IRT equating; subgroup equating; subscore equating; generalized partial credit model; mixture Rasch model; MCMC estimation
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