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Magis, David; De Boeck, Paul – Educational and Psychological Measurement, 2014
It is known that sum score-based methods for the identification of differential item functioning (DIF), such as the Mantel-Haenszel (MH) approach, can be affected by Type I error inflation in the absence of any DIF effect. This may happen when the items differ in discrimination and when there is item impact. On the other hand, outlier DIF methods…
Descriptors: Test Bias, Statistical Analysis, Test Items, Simulation
Magis, David; Tuerlinckx, Francis; De Boeck, Paul – Journal of Educational and Behavioral Statistics, 2015
This article proposes a novel approach to detect differential item functioning (DIF) among dichotomously scored items. Unlike standard DIF methods that perform an item-by-item analysis, we propose the "LR lasso DIF method": logistic regression (LR) model is formulated for all item responses. The model contains item-specific intercepts,…
Descriptors: Test Bias, Test Items, Regression (Statistics), Scores
De Boeck, Paul; Cho, Sun-Joo; Wilson, Mark – Applied Psychological Measurement, 2011
The models used in this article are secondary dimension mixture models with the potential to explain differential item functioning (DIF) between latent classes, called latent DIF. The focus is on models with a secondary dimension that is at the same time specific to the DIF latent class and linked to an item property. A description of the models…
Descriptors: Test Bias, Models, Statistical Analysis, Computation
Magis, David; De Boeck, Paul – Educational and Psychological Measurement, 2012
The identification of differential item functioning (DIF) is often performed by means of statistical approaches that consider the raw scores as proxies for the ability trait level. One of the most popular approaches, the Mantel-Haenszel (MH) method, belongs to this category. However, replacing the ability level by the simple raw score is a source…
Descriptors: Test Bias, Data, Error of Measurement, Raw Scores
Facon, Bruno; Magis, David; Nuchadee, Marie-Laure; De Boeck, Paul – Intelligence, 2011
Standardized tests are used widely in comparative studies of clinical populations, either as dependent or control variables. Yet, one cannot always be sure that the test items measure the same constructs in the groups under study. In the present work, 460 participants with intellectual disability of undifferentiated etiology and 488 typical…
Descriptors: Intelligence Tests, Standardized Tests, Mental Retardation, Children
Magis, David; De Boeck, Paul – Multivariate Behavioral Research, 2011
We focus on the identification of differential item functioning (DIF) when more than two groups of examinees are considered. We propose to consider items as elements of a multivariate space, where DIF items are outlying elements. Following this approach, the situation of multiple groups is a quite natural case. A robust statistics technique is…
Descriptors: Test Bias, Mathematics Tests, Identification, Sampling
Frederickx, Sofie; Tuerlinckx, Francis; De Boeck, Paul; Magis, David – Journal of Educational Measurement, 2010
In this paper we present a new methodology for detecting differential item functioning (DIF). We introduce a DIF model, called the random item mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is assumed for the item difficulties such that the…
Descriptors: Test Bias, Models, Test Items, Difficulty Level
Kahraman, Nilufer; De Boeck, Paul; Janssen, Rianne – International Journal of Testing, 2009
This study introduces an approach for modeling multidimensional response data with construct-relevant group and domain factors. The item level parameter estimation process is extended to incorporate the refined effects of test dimension and group factors. Differences in item performances over groups are evaluated, distinguishing two levels of…
Descriptors: Test Bias, Test Items, Groups, Interaction
Van den Noortgate, Wim; De Boeck, Paul – Journal of Educational and Behavioral Statistics, 2005
Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model…
Descriptors: Test Bias, Item Response Theory, Educational Assessment, Mathematical Models