Approximate Functional Relationship between IRT and CTT Item Discrimination Indices: A Simulation, Validation, and Practical Extension of Lord's (1980) Formula.

Journal of applied measurement Pub Date : 2017-01-01
John T Kulas, Jeffrey A Smith, Hui Xu
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引用次数: 0

Abstract

Lord (1980) presented a purely conceptual equation to approximate the nonlinear functional relationship between classical test theory (CTT; aka true score theory) and item response theory (IRT) item discrimination indices. The current project proposes a modification to his equation that makes it useful in practice. The suggested modification acknowledges the more common contemporary CTT discrimination index of a corrected item-total correlation and incorporates item difficulty. We simulated slightly over 768 trillion individual item responses to uncover a best-fitting empirical function relating the IRT and CTT discrimination indices. To evaluate the effectiveness of the function, we applied it to real-world test data from 16 workforce and educational tests. Our modification results in shifted functional asymptotes, slopes, and points of inflection across item difficulties. Validation with the workforce and educational tests suggests good prediction under common assumption testing conditions (approximately normal distribution of abilities and moderate item difficulties) and greater precision than Lord's (1980) formula.

IRT和CTT项目判别指标的近似函数关系:Lord(1980)公式的模拟、验证和实用推广。
Lord(1980)提出了一个纯概念方程来近似经典测试理论(CTT;即真分理论)和项目反应理论(IRT)的项目判别指标。目前的项目提出了对他的方程的修改,使其在实践中有用。建议的修改承认更常见的当代CTT区分指数的纠正项目-总相关和纳入项目难度。我们模拟了略超过768万亿的个别项目反应,以揭示与IRT和CTT歧视指数相关的最佳拟合经验函数。为了评估该函数的有效性,我们将其应用于来自16个劳动力和教育测试的真实测试数据。我们的修改导致在项目困难的功能渐近线,斜率和拐点移位。劳动力和教育测试的验证表明,在一般假设测试条件下(能力近似正态分布,项目难度适中)有很好的预测效果,并且比Lord(1980)公式的精度更高。
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