利用IRT残差DIF方法检测CAT中不同项目的功能

IF 1.4 4区 心理学 Q3 PSYCHOLOGY, APPLIED
Hwanggyu Lim, Edison M. Choe
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引用次数: 0

摘要

残差项目功能(RDIF)检测框架是近年来在线性测试环境下发展起来的。为了探索这一框架在计算机化自适应测试(CAT)中的潜在应用,本研究调查了RDIFR统计量作为检测CAT预试项目均匀DIF的指标和作为均匀DIF效应大小的直接测量的效用。广泛的CAT模拟表明,与CATSIB相比,RDIFR具有良好控制的I型误差,并且检测均匀DIF的能力略高,特别是当使用固定项目参数校准预测项目时。此外,RDIFR准确地估计了均匀DIF的量,而不考虑是否存在冲击。因此,RDIFR显示了其作为评估CAT中均匀DIF的统计和实际意义的有用工具的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting Differential Item Functioning in CAT Using IRT Residual DIF Approach

The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIFR statistic both as an index for detecting uniform DIF of pretest items in CAT and as a direct measure of the effect size of uniform DIF. Extensive CAT simulations revealed RDIFR to have well-controlled Type I error and slightly higher power to detect uniform DIF compared with CATSIB, especially when pretest items were calibrated using fixed-item parameter calibration. Moreover, RDIFR accurately estimated the amount of uniform DIF irrespective of the presence of impact. Therefore, RDIFR demonstrates its potential as a useful tool for evaluating both the statistical and practical significance of uniform DIF in CAT.

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来源期刊
CiteScore
2.30
自引率
7.70%
发文量
46
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.
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