Effect of Differential Item Functioning on Computer Adaptive Testing Under Different Conditions.

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL Applied Psychological Measurement Pub Date : 2024-11-01 Epub Date: 2024-09-17 DOI:10.1177/01466216241284295
Merve Sahin Kursad, Seher Yalcin
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Abstract

This study provides an overview of the effect of differential item functioning (DIF) on measurement precision, test information function (TIF), and test effectiveness in computer adaptive tests (CATs). Simulated data for the study was produced and analyzed with the Rstudio. During the data generation process, item pool size, DIF type, DIF percentage, item selection method for CAT, and the test termination rules were considered changed conditions. Sample size and ability parameter distribution, Item Response Theory (IRT) model, DIF size, ability estimation method, test starting rule, and item usage frequency method regarding CAT conditions were considered fixed conditions. To examine the effect of DIF, measurement precision, TIF and test effectiveness were calculated. Results show DIF has negative effects on measurement precision, TIF, and test effectiveness. In particular, statistically significant effects of the percentage DIF items and DIF type are observed on measurement precision.

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不同条件下差异化项目功能对计算机自适应测试的影响
本研究概述了差异项目功能(DIF)对计算机自适应测试(CAT)中测量精度、测试信息功能(TIF)和测试有效性的影响。本研究使用 Rstudio 生成和分析模拟数据。在数据生成过程中,项目池规模、DIF 类型、DIF 百分比、CAT 项目选择方法和测试终止规则被视为变化条件。样本量和能力参数分布、项目反应理论(IRT)模型、DIF 大小、能力估计方法、测试开始规则以及有关 CAT 条件的项目使用频率方法被视为固定条件。为了考察 DIF 的影响,计算了测量精度、TIF 和测试有效性。结果表明,DIF 对测量精度、TIF 和测验有效性有负面影响。特别是,DIF 项目百分比和 DIF 类型对测量精度的影响在统计学上具有显著性。
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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.
期刊最新文献
Effect of Differential Item Functioning on Computer Adaptive Testing Under Different Conditions. Evaluating the Construct Validity of Instructional Manipulation Checks as Measures of Careless Responding to Surveys. A Mark-Recapture Approach to Estimating Item Pool Compromise. Estimating Test-Retest Reliability in the Presence of Self-Selection Bias and Learning/Practice Effects. The Improved EMS Algorithm for Latent Variable Selection in M3PL Model.
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