Using Item Scores and Distractors in Person-Fit Assessment

IF 1.4 4区心理学 Q3 PSYCHOLOGY, APPLIED

Journal of Educational Measurement Pub Date : 2022-09-16 DOI:10.1111/jedm.12345

Kylie Gorney, James A. Wollack

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引用次数: 3

Abstract

In order to detect a wide range of aberrant behaviors, it can be useful to incorporate information beyond the dichotomous item scores. In this paper, we extend the $l_{z}$ and $l_{z}^{*}$ person-fit statistics so that unusual behavior in item scores and unusual behavior in item distractors can be used as indicators of aberrance. Through detailed simulations, we show that the new statistics are more powerful than existing statistics in detecting several types of aberrant behavior, and that they are able to control the Type I error rate in instances where the model does not exactly fit the data. A real data example is also provided to demonstrate the utility of the new statistics in an operational setting.

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在个人适合度评估中使用项目分数和干扰因素

为了检测大范围的异常行为，将二分项目得分以外的信息结合起来可能是有用的。本文扩展了l z$ l_z$和l z *$ l_z^*$的人拟合统计量，使得项目分数中的异常行为和项目干扰物中的异常行为可以作为异常的指标。通过详细的模拟，我们表明新的统计数据在检测几种异常行为方面比现有的统计数据更强大，并且在模型不完全适合数据的情况下，它们能够控制I型错误率。还提供了一个真实的数据示例，以演示新统计数据在操作设置中的实用性。

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来源期刊

Journal of Educational Measurement Multiple-

CiteScore

2.30

自引率

7.70%

发文量

期刊介绍： The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.