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Applied Psychological Measurement
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Multidimensionality and Item Bias in Item Response Theory

T.C. Oshima

Georgia State University

M. David Miller

University of Florida

This paper demonstrates empirically how item bias indexes based on item response theory (IRT) identify bias that results from multidimensionality. When a test is multidimensional (MD) with a primary trait and a nuisance trait that affects a small portion of the test, item bias is defined as a mean difference on the nuisance trait between two groups. Results from a simulation study showed that although IRT-based bias indexes clearly distinguished multidimensionality from item bias, even with the presence of a between-group dif ference on the primary trait, the bias detection rate depended on the degree to which the item measured the nuisance trait, the values of MD discrimination, and the number of MD items. It was speculated that bias defined from the MD perspective was more likely to be detected when the test data met the essential unidimensionality assumption. Index

Key Words: terms: item bias • multidimensionality • item response theory • item bias • mean differences • multidimensionality; multidimensionality • mean differences in IRT.

Applied Psychological Measurement, Vol. 16, No. 3, 237-248 (1992)
DOI: 10.1177/014662169201600304


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This article has been cited by other articles:


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Applied Psychological MeasurementHome page
K. M. Mazor, R. K. Hambleton, and B. E. Clauser
Multidimensional DIF Analyses: The Effects of Matching on Unidimensional Subtest Scores
Applied Psychological Measurement, December 1, 1998; 22(4): 357 - 367.
[Abstract] [PDF]


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Applied Psychological MeasurementHome page
M. D. Miller and T.C. Oshima
Effect of Sample Size, Number of Biased Items, and Magnitude of Bias on a Two-Stage Item Bias Estimation Method
Applied Psychological Measurement, December 1, 1992; 16(4): 381 - 388.
[PDF]