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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
Lee, HyeSun; Geisinger, Kurt F. – Educational and Psychological Measurement, 2016
The current study investigated the impact of matching criterion purification on the accuracy of differential item functioning (DIF) detection in large-scale assessments. The three matching approaches for DIF analyses (block-level matching, pooled booklet matching, and equated pooled booklet matching) were employed with the Mantel-Haenszel…
Descriptors: Test Bias, Measurement, Accuracy, Statistical Analysis
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
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
DeMars, Christine E. – Journal of Educational and Behavioral Statistics, 2009
The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…
Descriptors: Regression (Statistics), Test Bias, Error of Measurement, True Scores