Item-Fit Statistic Based on Posterior Probabilities of Membership in Ability Groups.

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Bartosz Kondratek
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引用次数: 3

Abstract

A novel approach to item-fit analysis based on an asymptotic test is proposed. The new test statistic, χ w 2 , compares pseudo-observed and expected item mean scores over a set of ability bins. The item mean scores are computed as weighted means with weights based on test-takers' a posteriori density of ability within the bin. This article explores the properties of χ w 2 in case of dichotomously scored items for unidimensional IRT models. Monte Carlo experiments were conducted to analyze the performance of χ w 2 . Type I error of χ w 2   was acceptably close to the nominal level and it had greater power than Orlando and Thissen's S - x 2 . Under some conditions, power of χ w 2 also exceeded the one reported for the computationally more demanding Stone's χ 2 .

基于能力组隶属度后验概率的项目拟合统计。
提出了一种基于渐近检验的项目拟合分析新方法。新的检验统计量χ w 2比较了一组能力箱上的伪观察和预期项目平均得分。项目平均得分以加权平均数计算,权重基于考生在bin中的后验能力密度。本文探讨了单维IRT模型中二分类得分项目的χ w 2的性质。通过蒙特卡罗实验对χ w2的性能进行了分析。χ w 2的I型误差可接受地接近名义水平,其功率大于Orlando和Thissen的S - x2。在某些条件下,χ w 2的幂也超过了计算要求更高的Stone的χ 2 *所报告的幂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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