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Nonuniform DIF Detection using Discriminant Logistic Analysis and Multinomial Logistic Regression: A comparison for polytomous items

机译:使用判别逻辑分析和多项式逻辑回归的非均匀DIF检测:多项项目的比较

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摘要

This study focused on the effectiveness in nonuniform polytomous item DIF detection using Discriminant Logistic Analysis (DLA) and Multinomial Logistic Regression (MLR). A computer simulation study was conducted to compare the effect of using DLA and MLR, applying either an iterative test purification procedure or non-iterative to detect nonuniform DIF. The conditions under study were: DIF effect size (0.5, 1.0 and 1.5), sample size (500 and 1000), percentage of DIF items in the test (0, 10 and 20%) and DIF type (nonuniform). The results suggest that DLA is more accurate than MLR in detecting DIF. However, the purification process only improved the correct detection rate when MLR was applied. The false positive rates for both procedures were similar. Moreover, when the test purification procedure was used, the proportion of non-DIF items that were detected as DIF decreased for both procedures, although the false positive rates were smaller for DLA than for MLR.
机译:这项研究的重点是使用判别逻辑分析(DLA)和多项式逻辑回归(MLR)进行非均匀多项项目DIF检测的有效性。进行了计算机模拟研究,以比较使用DLA和MLR的效果,应用迭代测试纯化程序或非迭代检测非均匀DIF。研究的条件是:DIF影响大小(0.5、1.0和1.5),样本大小(500和1000),测试中DIF项目的百分比(0%,10%和20%)和DIF类型(不均匀)。结果表明,在检测DIF方面,DLA比MLR更准确。但是,当应用MLR时,纯化过程只会提高正确的检测率。两种方法的假阳性率相似。此外,当使用测试纯化程序时,虽然这两种方法的DLA假阳性率均小于MLR,但两种方法都将检测为DIF的非DIF项目的比例降低。

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