Three new corrections for standardized person-fit statistics for tests with polytomous items

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS British Journal of Mathematical & Statistical Psychology Pub Date : 2024-04-17 DOI:10.1111/bmsp.12342
Kylie Gorney
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Abstract

Recent years have seen a growing interest in the development of person-fit statistics for tests with polytomous items. Some of the most popular person-fit statistics for such tests belong to the class of standardized person-fit statistics, T , that is assumed to have a standard normal null distribution. However, this distribution only holds when (a) the true ability parameter is known and (b) an infinite number of items are available. In practice, both conditions are violated, and the quality of person-fit results is expected to deteriorate. In this paper, we propose three new corrections for T that simultaneously account for the use of an estimated ability parameter and the use of a finite number of items. The three new corrections are direct extensions of those that were developed by Gorney et al. (Psychometrika, 2024, https://doi.org/10.1007/s11336-024-09960-x) for tests with only dichotomous items. Our simulation study reveals that the three new corrections tend to outperform not only the original statistic T but also an existing correction for T proposed by Sinharay (Psychometrika, 2016, 81, 992). Therefore, the new corrections appear to be promising tools for assessing person fit in tests with polytomous items.

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针对多项式项目测试的标准化人称拟合统计的三种新修正方法
近些年来,人们对开发多变量项目测验的人称拟合统计量越来越感兴趣。此类测验中一些最常用的拟合统计量属于标准化拟合统计量,即假定具有标准正态空分布的拟合统计量。然而,这种分布只有在以下情况下才成立:(a) 真正的能力参数已知;(b) 有无限多的项目可用。在实践中,这两个条件都会被违反,从而导致拟人结果的质量下降。在本文中,我们提出了三种新的修正方法,同时考虑到使用估计的能力参数和使用有限数量的项目。这三种新的修正方法是 Gorney 等人(Psychometrika, 2024, https://doi.org/10.1007/s11336-024-09960-x)针对只有二分项目的测验所开发的修正方法的直接扩展。我们的模拟研究显示,这三种新的校正不仅往往优于原始统计量,而且也优于辛哈雷(Sinharay)提出的现有校正(Psychometrika,2016,81,992)。因此,新的校正似乎是评估多项式项目测试中的人称契合度的有前途的工具。
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来源期刊
CiteScore
5.00
自引率
3.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including: • mathematical psychology • statistics • psychometrics • decision making • psychophysics • classification • relevant areas of mathematics, computing and computer software These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.
期刊最新文献
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