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Lee, Soo; Bulut, Okan; Suh, Youngsuk – Educational and Psychological Measurement, 2017
A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory…
Descriptors: Test Bias, Test Items, Models, Item Response Theory
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Lee, Yi-Hsuan; Zhang, Jinming – International Journal of Testing, 2017
Simulations were conducted to examine the effect of differential item functioning (DIF) on measurement consequences such as total scores, item response theory (IRT) ability estimates, and test reliability in terms of the ratio of true-score variance to observed-score variance and the standard error of estimation for the IRT ability parameter. The…
Descriptors: Test Bias, Test Reliability, Performance, Scores
James, Syretta R.; Liu, Shihching Jessica; Maina, Nyambura; Wade, Julie; Wang, Helen; Wilson, Heather; Wolanin, Natalie – Montgomery County Public Schools, 2021
The impact of the COVID-19 pandemic continues to overwhelm the functioning and outcomes of educational systems throughout the nation. The public education system is under particular scrutiny given that students, families, and educators are under considerable stress to maintain academic progress. Since the beginning of the crisis, school-systems…
Descriptors: Achievement Tests, COVID-19, Pandemics, Public Schools
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Atalay Kabasakal, Kübra; Arsan, Nihan; Gök, Bilge; Kelecioglu, Hülya – Educational Sciences: Theory and Practice, 2014
This simulation study compared the performances (Type I error and power) of Mantel-Haenszel (MH), SIBTEST, and item response theory-likelihood ratio (IRT-LR) methods under certain conditions. Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying…
Descriptors: Comparative Analysis, Item Response Theory, Statistical Analysis, Test Bias