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Lee, HyeSun; Geisinger, Kurt F. – International Journal of Testing, 2014
Differential item functioning (DIF) analysis is important in terms of test fairness. While DIF analyses have mainly been conducted with manifest grouping variables, such as gender or race/ethnicity, it has been recently claimed that not only the grouping variables but also contextual variables pertaining to examinees should be considered in DIF…
Descriptors: Test Bias, Gender Differences, Regression (Statistics), Statistical Analysis
Ong, Yoke Mooi; Williams, Julian; Lamprianou, Iasonas – International Journal of Testing, 2015
The purpose of this article is to explore crossing differential item functioning (DIF) in a test drawn from a national examination of mathematics for 11-year-old pupils in England. An empirical dataset was analyzed to explore DIF by gender in a mathematics assessment. A two-step process involving the logistic regression (LR) procedure for…
Descriptors: Mathematics Tests, Gender Differences, Test Bias, Test Items
Wyse, Adam E.; Mapuranga, Raymond – International Journal of Testing, 2009
Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…
Descriptors: Test Bias, Evaluation Methods, Test Items, Educational Assessment

Zimmerman, Donald W.; Zumbo, Bruno D. – International Journal of Testing, 2001
Presents a model of tests and measurement that identifies test scores with Hilbert space vectors and true and error components of scores with linear operators. This geometric point of view brings to light relations among elementary concepts in test theory, including reliability, validity, and parallel tests. (Author/SLD)
Descriptors: Models, Probability, Reliability, Scores
Dirkzwager, Arie – International Journal of Testing, 2003
The crux in psychometrics is how to estimate the probability that a respondent answers an item correctly on one occasion out of many. Under the current testing paradigm this probability is estimated using all kinds of statistical techniques and mathematical modeling. Multiple evaluation is a new testing paradigm using the person's own personal…
Descriptors: Psychometrics, Probability, Models, Measurement