Title
Multidimensionality and item bias in item response theory
Abstract
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 difference
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
terms: item bias, multidimensionality; item response
theory, item bias, mean differences, multidimensionality;
multidimensionality; mean differences in IRT.
Identifiers
other: doi:10.1177/014662169201600304
Previously Published Citation
Oshima, T. C & Miller, M. David. (1992). Multidimensionality and item bias in item response theory. Applied Psychological Measurement, 16, 237-248. doi:10.1177/014662169201600304
Suggested Citation
Oshima, T. C.; Miller, M. David.
(1992).
Multidimensionality and item bias in item response theory.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/115652.