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来源类型Publication
Shrinkage of Value-Added Estimates and Characteristics of Students with Hard-to-Predict Achievement Levels (Journal Article)
Mariesa Herrmann; Elias Walsh; and Eric Isenberg
发表日期2016-05-04
出版者Statistics and Public Policy, vol. 3, issue 1 (published online ahead of print, subscription required)
出版年2016
语种英语
概述This article investigates how shrinkage affects the value-added estimates of teachers of hard-to-predict students.",
摘要It is common in the implementation of teacher accountability systems to use empirical Bayes shrinkage to adjust teacher value-added estimates by their level of precision. Because value-added estimates based on fewer students and students with “hard-to-predict” achievement will be less precise, the procedure could have differential impacts on the probability that the teachers of fewer students or students with hard-to-predict achievement will be assigned consequences. This article investigates how shrinkage affects the value-added estimates of teachers of hard-to-predict students. We found that teachers of students with low prior achievement and who receive free lunch tend to have less precise value-added estimates. However, in our sample, shrinkage had no statistically significant effect on the relative probability that teachers of hard-to-predict students received consequences.
URLhttps://www.mathematica.org/our-publications-and-findings/publications/ja-shrinkage-of-valueadded-estimates-and-characteristics-of-students-with-hardtopredict
来源智库Mathematica Policy Research (United States)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/488490
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Mariesa Herrmann,Elias Walsh,and Eric Isenberg. Shrinkage of Value-Added Estimates and Characteristics of Students with Hard-to-Predict Achievement Levels (Journal Article). 2016.
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