Improving Mantel–Haenszel DIF Estimation Through Bayesian Updating

Rebecca Zwick, Lei Ye and Steven Isham

Journal of Educational and Behavioral Statistics, 2012, vol. 37, issue 5, 601-629

Abstract: This study demonstrates how the stability of Mantel–Haenszel (MH) DIF (differential item functioning) methods can be improved by integrating information across multiple test administrations using Bayesian updating (BU). The authors conducted a simulation that showed that this approach, which is based on earlier work by Zwick, Thayer, and Lewis, can yield more accurate DIF estimation and improve the detection of DIF items, even when compared to other approaches that aggregate data across administrations. The authors also applied the method to data from several college-level tests. The BU approach provides a natural way to accumulate all known DIF information about each test item while mitigating the undesirable bias toward zero that affected the performance of two previous Bayesian DIF methods.

Keywords: differential item functioning; test fairness; Bayesian methods (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998611431085 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:37:y:2012:i:5:p:601-629

DOI: 10.3102/1076998611431085

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().