IRT item bias detection procedures: Issues of model misspecification, robustness, and parameter linking

Lautenschlager, Gary J.
Park, Dong-gun
1988
Thumbnail Image

View/Download File

v12n4p365.pdf (1.57 MB)

Persistent link to this item

https://hdl.handle.net/11299/104311
Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

IRT item bias detection procedures: Issues of model misspecification, robustness, and parameter linking

Authors

Published Date

1988

Publisher

Type

Article

Abstract

This article examines the consequences of employing IRT item bias detection procedures with multidimensional IRT item data. Parameter linking methods used in previous studies of item bias were investigated in a simulation that minimized the need for such linking. The results illustrate shortcomings of two linking methods that have been employed in IRT item bias detection studies. The effectiveness of these methods depended on several factors, including the number of biased items in a fixed-length test, whether bias was against only one group or more than one group, and the correlation between the two latent abilities. The findings indicated that some current IRT-based statistical procedures for detecting item bias were not generally effective at differentiating biased from unbiased items. Index terms: item bias, item response theory, multidimensional IRT data, parameter linking, reverse bias, statistical artifacts.

Keywords

Description

Related to

Replaces

License

Collections

Applied Psychological Measurement, Volume 12, 1988

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Lautenschlager, Gary J & Park, Dong-gun. (1988). IRT item bias detection procedures: Issues of model misspecification, robustness, and parameter linking. Applied Psychological Measurement, 12, 365-376. doi:10.1177/014662168801200404

Suggested citation

Lautenschlager, Gary J.; Park, Dong-gun. (1988). IRT item bias detection procedures: Issues of model misspecification, robustness, and parameter linking. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/104311.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.