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Identification of Differential Item Functioning in Multiple-Group Settings: A Multivariate Outlier Detection Approach

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Title: Identification of Differential Item Functioning in Multiple-Group Settings: A Multivariate Outlier Detection Approach
Language: English
Authors: Magis, David, De Boeck, Paul
Source: Multivariate Behavioral Research. 2011 46(5):733-755.
Availability: Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Physical Description: PDF
Page Count: 23
Publication Date: 2011
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Descriptors: Test Bias, Mathematics Tests, Identification, Sampling, Evaluation Methods, Assistive Technology, Calculators, Multivariate Analysis, College Students, College Mathematics
DOI: 10.1080/00273171.2011.606757
ISSN: 0027-3171
Abstract: 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 proposed to identify DIF items as outliers in the multivariate space. For low dimensionalities, up to 2-3 groups, a simple graphical tool is derived. We illustrate our approach with a reanalysis of data from Kim, Cohen, and Park (1995) on using calculators for a mathematics test. (Contains 2 tables and 4 figures.)
Abstractor: As Provided
Number of References: 38
Entry Date: 2011
Accession Number: EJ948266
Database: ERIC
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  Data: 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 proposed to identify DIF items as outliers in the multivariate space. For low dimensionalities, up to 2-3 groups, a simple graphical tool is derived. We illustrate our approach with a reanalysis of data from Kim, Cohen, and Park (1995) on using calculators for a mathematics test. (Contains 2 tables and 4 figures.)
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