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使用拉施模型检测项目偏差。

Detecting item bias with the Rasch model.

作者信息

Smith Richard M

机构信息

Data Recognition Corporation.

出版信息

J Appl Meas. 2004;5(4):430-49.

Abstract

The purpose of this article is to introduce the concept of item bias, highlighting the differences between the definition of the term as it is used within Rasch measurement and the definition of the term as it is used in the true-score model, non-model based approaches, or multi-item parameter latent trait models. The discussion continues with a description of alternative methods of assessing item bias within the Rasch measurement framework and discusses the power of these methods to detect the presence of item bias. The discussion concludes with several examples drawn from a number of different mathematics tests. This includes a comparison of the Rasch separate calibration t-test and the Mantel-Haenszel approaches.

摘要

本文旨在介绍项目偏差的概念,强调该术语在拉施测量中使用的定义与在真分数模型、非基于模型的方法或多项目参数潜在特质模型中使用的定义之间的差异。讨论接着描述了在拉施测量框架内评估项目偏差的替代方法,并讨论了这些方法检测项目偏差存在的能力。讨论以从多个不同数学测试中提取的几个例子作为结束。这包括拉施单独校准t检验和曼特尔-亨塞尔方法的比较。

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