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Zwick, Rebecca; Ye, Lei; Isham, Steven – Journal of Educational Measurement, 2018
In typical differential item functioning (DIF) assessments, an item's DIF status is not influenced by its status in previous test administrations. An item that has shown DIF at multiple administrations may be treated the same way as an item that has shown DIF in only the most recent administration. Therefore, much useful information about the…
Descriptors: Test Bias, Testing, Test Items, Bayesian Statistics
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Guler, Nese; Penfield, Randall D. – Journal of Educational Measurement, 2009
In this study, we investigate the logistic regression (LR), Mantel-Haenszel (MH), and Breslow-Day (BD) procedures for the simultaneous detection of both uniform and nonuniform differential item functioning (DIF). A simulation study was used to assess and compare the Type I error rate and power of a combined decision rule (CDR), which assesses DIF…
Descriptors: Test Bias, Simulation, Test Items, Measurement
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Thorndike, Robert L. – Journal of Educational Measurement, 1971
Descriptors: Culture Fair Tests, Predictive Measurement, Test Bias, Test Reliability
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Bolt, Daniel M.; Gierl, Mark J. – Journal of Educational Measurement, 2006
Inspection of differential item functioning (DIF) in translated test items can be informed by graphical comparisons of item response functions (IRFs) across translated forms. Due to the many forms of DIF that can emerge in such analyses, it is important to develop statistical tests that can confirm various characteristics of DIF when present.…
Descriptors: Regression (Statistics), Tests, Test Bias, Test Items
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Moss, Jacque D.; Brown, Frederick G. – Journal of Educational Measurement, 1979
This study investigated the hypothesis that sex biases (defined as disproportionate references to one sex) in a reading passage and on a comprehension test would lead to differential performance by 120 male and female undergraduates. An analysis of variance revealed no significant main effects or interactions. (Author/CTM)
Descriptors: Analysis of Variance, Content Analysis, Higher Education, Reading Comprehension