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  • 标题:Using Graphical Models to Examine Value-Added Models
  • 本地全文:下载
  • 作者:Daniel B. Wright
  • 期刊名称:Statistics and Public Policy
  • 电子版ISSN:2330-443X
  • 出版年度:2017
  • 卷号:4
  • 期号:In Progress
  • 页码:1-7
  • DOI:10.1080/2330443X.2017.1294037
  • 出版社:Taylor and Francis Ltd
  • 摘要:ABSTRACT Value-added models (VAMs) of student test scores are used within education because they are supposed to measure school and teacher effectiveness well. Much research has compared VAM estimates for different models, with different measures (e.g., observation ratings), and in experimental designs. VAMs are considered here from the perspective of graphical models and situations are identified that are problematic for VAMs. If the previous test scores are influenced by variables that also influence the true effectiveness of the school/teacher and there are variables that influence both the previous and current test scores, then the estimates of effectiveness can be poor. Those using VAMs should consider the models that may give rise to their data and evaluate their methods for these models before using the results for high-stakes decisions.
  • 关键词:Bayes nets ; Causality ; Directed acyclic graphs ; School effectiveness ; Teacher effectiveness
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