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A Mixture Model Analysis of Differential Item Functioning
Abstract
Once a differential item functioning (DIF) item has been identified, little is known about the examinees for whom the item functions differentially. This is because DIF focuses on manifest group characteristics that are associated with it, but do not explain why examinees respond differentially to items. We first analyze item response patterns for gender DIF and then illustrate, through the use of a mixture item response theory (IRT) model, how the manifest characteristic associated with DIF often has a very weak relationship with the latent groups actually being advantaged or disadvantaged by the item(s). Next, we propose an alternative approach to DIF assessment that first uses an exploratory mixture model analysis to define the primary dimension(s) that contribute to DIF, and secondly studies examinee characteristics associated with those dimensions in order to understand the cause(s) of DIF. Comparison of academic characteristics of these examinees across classes reveals some clear differences in manifest characteristics between groups.
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Cited by
Item Response Theory and Clinical Measurement
Reise, S. P., & Waller, N. G. (2009) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.032408.153553 · Cited by 719
Measuring progressions: Assessment structures underlying a learning progression
Wilson, M. (2009) · Journal of Research in Science Teaching · doi:10.1002/tea.20318 · Cited by 329
A signal detection–item response theory model for evaluating neuropsychological measures
Thomas, M. L., Brown, G. G., Gur, R. C., Moore, T. M., Patt, V. M., Risbrough, V. B., & Baker, D. G. (2018) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2018.1427699 · Cited by 22
Metadata
- Authors
- Cohen, A. S., & Bolt, D. M.
- Venue
- Journal of Educational Measurement
- Publisher
- Wiley
- Published
- 2005-05-26
- Volume
- 42
- Issue
- 2
- Pages
- 133-148
- ISSN
- 0022-0655 (ISSN-L)
- 1745-3984
- OpenAlex
- W2038464711
- Cited by
- 205
- References
- 0
- FWCI
- 5.23
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.