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Journal of Educational Measurement, 1992
Many researchers have suggested that the main cause of item bias is the misspecification of the latent ability space, where items that measure multiple abilities are scored as though they are measuring a single ability. If two different groups of examinees have different underlying multidimensional ability distributions and the test items are capable ...
Terry A. Ackerman
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Many researchers have suggested that the main cause of item bias is the misspecification of the latent ability space, where items that measure multiple abilities are scored as though they are measuring a single ability. If two different groups of examinees have different underlying multidimensional ability distributions and the test items are capable ...
Terry A. Ackerman
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VALIDITY OF APPROXIMATION TECHNIQUES FOR DETECTING ITEM BIAS
Journal of Educational Measurement, 1985The purpose of this research was to recommend an item bias procedure when the number of minority examinees is too small to use preferred three‐parameter IRT methods. The chi‐square, Angoff delta‐plot, andpseudo‐IRT indices were compared with both real and simulated data.
David M. Williams +2 more
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EMPIRICAL COMPARISON OF SELECTED ITEM BIAS DETECTION PROCEDURES WITH BIAS MANIPULATION
Journal of Educational Measurement, 1984Biased test items were intentionally imbedded within a set of test items, and the resulting instrument was administered to large samples of blacks and whites. Three popular item bias detection procedures were then applied to the data: (1) the three‐parameter item characteristic curve procedure, (2) the chi‐square method, and (3) the transformed item ...
Gail Ironson +3 more
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Evidence of item bias in a national flourishing measure for autistic youth
Autism Research, 2023Flourishing is a positive health indicator that aligns with strengths‐based perspectives and measures within autism research. Flourishing indicators were recently included in the National Survey of Children's Health (NSCH) and have been used to evidence ...
S. Ross +3 more
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Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020Recommendation algorithms typically build models based on user-item interactions (e.g., clicks, likes, or ratings) to provide a personalized ranked list of items.
Ziwei Zhu, Jianling Wang, James Caverlee
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Sampling-bias-corrected neural modeling for large corpus item recommendations
ACM Conference on Recommender Systems, 2019Many recommendation systems retrieve and score items from a very large corpus. A common recipe to handle data sparsity and power-law item distribution is to learn item representations from its content features. Apart from many content-aware systems based
Xinyang Yi +8 more
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Research Synthesis Methods, 2017
To assess the conditions under which employing an overview of systematic reviews is likely to lead to a high risk of bias.
Madeleine Ballard, P. Montgomery
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To assess the conditions under which employing an overview of systematic reviews is likely to lead to a high risk of bias.
Madeleine Ballard, P. Montgomery
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, 2014
In educational measurement, responses of students on items are used not only to measure the ability of students, but also to evaluate and compare the performance of schools.
Margot Bennink +3 more
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In educational measurement, responses of students on items are used not only to measure the ability of students, but also to evaluate and compare the performance of schools.
Margot Bennink +3 more
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Test for item bias in a quality of life questionnaire
Journal of Clinical Epidemiology, 1995Item bias (differential item functioning) analysis examines whether the construction of an index from two or more variables results in bias in relation to sex, age, or other criteria. Item bias may lead to erroneous conclusions because of distortion or dilution of the effects measured.
Grønvold, Mogens +3 more
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Item bias and item response theory
International Journal of Educational Research, 1989Abstract In this chapter the definition, detection, and explanation of item bias is discussed. Item bias is generally defined as conditional dependence; within the framework of item response theory the general definition implies that the item characteristic curves of two groups do not coincide.
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