Item-fit evaluation in biased tests: a study under Rasch model

In this paper, the power rates and distributional properties of the Outfit, Infit, Lz, ECI2z and ECI4z statistics when they are used in tests with biased or differential item functioning (DIF) were explored. In this study, different conditions of sample size, sample size ratio focal and reference gr...

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Bibliographic Details
Published in:Quality & quantity 2011-04, Vol.45 (3), p.715-734
Main Authors: Hidalgo, M. Dolores, López-Pina, José A.
Format: Article
Language:English
Subjects:
Bias
Calibration
Error
Expected values
Item response theory
Methodology
Methodology of the Social Sciences
Power
Random variables
Rasch model
Reference Groups
Research Note
Samples
Social Sciences
Standard deviation
Statistics
Validity
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Summary:In this paper, the power rates and distributional properties of the Outfit, Infit, Lz, ECI2z and ECI4z statistics when they are used in tests with biased or differential item functioning (DIF) were explored. In this study, different conditions of sample size, sample size ratio focal and reference group, impact between groups, DIF effect size, and percentage of DIF items were manipulated. In addition, examinee responses were generated to simulate uniform DIF. Results suggest that item fit statistics generally detected medium percents of DIF in large samples (1000/500 or 1000/1000) only when DIF effect size was relatively high and when the mean of focal and reference group was different. Moreover, when groups had equal mean, low correct identification rates were found in the five item-fit indices. In general, the results showed adequate control of false positive rates. These findings lead to the conclusion that all indices used in this study are partially adequate fit measures for detecting biased items, mainly when impact between groups is present and sample size is large.
ISSN:0033-5177
1573-7845
DOI:10.1007/s11135-010-9318-8