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Identifying Local Dependence with a Score Test Statistic Based on the Bifactor 2-Parameter Logistic Model.

机译:基于双因子2参数Logistic模型的评分测试统计量识别本地依存关系。

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摘要

Local dependence (LD) refers to the violation of the local independence assumption of most item response models. Statistics that indicate LD between a pair of items on a test or questionnaire that is being fitted with an item response model can play a useful diagnostic role in applications of item response theory. In this paper a new score test statistic, Sb, for underlying LD (ULD) is proposed based on the bifactor 2-parameter logistic model. To compare the performance of Sb with the score test statistic (St) based on a threshold shift model for surface LD (SLD), and the LD X2 statistic, we simulated data under null, ULD, and SLD conditions, and evaluated the null distribution and power of each of these test statistics. The results summarize the null distributions of all three diagnostic statistics, and their power for approximately matched degrees of ULD and SLD. Future research directions are discussed, including the straightforward generalization of Sb for polytomous item response models, and the challenges involved in the corresponding generalizations of St and LD X2.
机译:局部依赖(LD)是指违反大多数项目响应模型的局部独立性假设。指示适合项目响应模型的测试或问卷上一对项目之间的LD的统计量可以在项目响应理论的应用中发挥有用的诊断作用。在本文中,基于双因素2参数逻辑模型,提出了针对基础LD(ULD)的新分数测试统计Sb。为了将Sb的性能与基于表面LD(SLD)的阈值偏移模型的得分测试统计量(St)和LD X2统计量进行比较,我们在空,ULD和SLD条件下模拟了数据,并评估了空分布以及每个测试统计信息的功能。结果总结了所有三个诊断统计数据的零分布,以及它们在近似匹配的ULD和SLD程度下的功效。讨论了未来的研究方向,包括对多项目反应模型进行Sb的直接推广,以及St和LD X2的相应推广所涉及的挑战。

著录项

  • 作者

    Liu, Yang.;

  • 作者单位

    The University of North Carolina at Chapel Hill.;

  • 授予单位 The University of North Carolina at Chapel Hill.;
  • 学科 Psychology Experimental.;Psychology Psychometrics.
  • 学位 M.A.
  • 年度 2011
  • 页码 29 p.
  • 总页数 29
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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