Estimating Population Characteristics From Sparse Matrix Samples of Item Responses
Estimating Population Characteristics From Sparse Matrix Samples of Item Responses
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从项目响应的稀疏矩阵样本估计总体特征
DOI：
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发表时间：
1992
期刊：
影响因子：
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通讯作者：
K. Sheehan
中科院分区：
文献类型：
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作者：
R. Mislevy;A. Beaton;Bruce Kaplan;K. Sheehan
多矩阵项目抽样设计，提供有关人口特征的信息，最有效地管理太少的反应，以估计他们的个人profitness的学生。边际估计程序，估计人口特征直接从项目的反应，必须采用实现这样的抽样设计的好处。通过构建一个全面的广泛的边际解的结果，学生专业知识的合理值的文件，可以获得各种各样的分析的适当的边际估计程序的数值近似。本文在一个简化的环境中发展了合理值背后的概念，概述了它们在国家教育进步评估（NAEP）中的使用，并用学术能力倾向测试（SAT）的数据说明了这种方法。
The multiple-matrix item sampling designs that provide information about population characteristics most efficiently administer too few responses to students to estimate their proficiencies individually. Marginal estimation procedures, which estimate population characteristics directly from item responses, must be employed to realize the benefits of such a sampling design. Numerical approximations of the appropriate marginal estimation procedures for a broad variety of analyses can be obtained by constructing, from the results of a comprehensive extensive marginal solution, files of plausible values of student proficiencies. This article develops the concepts behind plausible values in a simplified setting, sketches their use in the National Assessment of Educational Progress (NAEP), and illustrates the approach with data from the Scholastic Aptitude Test (SA T).