Using Loss Functions for DIF Detection: An Empirical Bayes Approach

By R. Zwick, Dorothy T. Thayer, C. Lewis. 2000

55 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/583dfe457841cedef79ec6453ef90288ff422eff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Randall D. Penfield
2. N. Dorans
3. R. Zwick
4. Minjeong Jeon
5. N. V. Dam
6. Wen-Chung Wang
7. Paul Holland
8. Anastassia Loukina

Citations in the corpus

• ETS CONTRIBUTIONS TO THE QUANTITATIVE ASSESSMENT OF ITEM, TEST, AND SCORE FAIRNESS (2013, methodology): “Zwick et al. (2000) proposed a Bayesian updating (BU) method that may avert the shrinkage associated with the EB and FB approaches.”
• A Review of ETS Differential Item Functioning Assessment Procedures: Flagging Rules, Minimum Sample Size Requirements, and Criterion Refinement (2012, methodology): “The EB loss function conservative rule is a variation on a rule developed by Zwick et al. (2000).”
• An Approach for Categorizing DIF in Polytomous Items (2007, methodology): “Although other cutoff values could be used in defining a DIF categorization scheme, those of the ETS scheme have been endorsed by numerous test developers, as evidenced by its widespread use in the educational measurement community (eg, Camilli & Shepard, 1994 ; Zieky, 1993 ; Zwick, Thayer, & Lew”