Variance Estimation for NAEP Data Using a Resampling-Based Approach: An Application of Cognitive Diagnostic Models. Research Report. ETS RR-10-26.

Variance Estimation for NAEP Data Using a Resampling-Based Approach: An Application of Cognitive Diagnostic Models. Research Report. ETS RR-10-26.
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使用基于重采样的方法对 NAEP 数据进行方差估计:认知诊断模型的应用。

DOI:
10.1002/j.2333-8504.2010.tb02233.x
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发表时间:
2010
期刊:
Educational Testing Service
影响因子:
--
通讯作者:
M. Davier
M. Davier
中科院分区:
--
文献类型:
--
作者:
Chueh;Xueli Xu;M. Davier

文献摘要

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本文提出了一种应用的刀切法方差估计的能力推断组的学生,使用一个多维离散模型的项目反应数据。用于证明该方法的数据来自国家教育进步评估(NAEP)。在NAEP中使用的操作方法,其中合理的值被用来进行能力推断,在本文中提出的方法重新估计模型的所有参数,并在不使用合理的值的情况下,重复样本的刀切的基础上进行能力推断。
This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach used in NAEP, where plausible values are used to make ability inferences, the approach presented in this paper reestimates all parameters of the model, and makes ability inferences based on replicate samples of the jackknife without using plausible values.