Effects of Average Signed Area Between Two Item Characteristic Curves and Test Purification Procedures on the DIF Detection via the Mantel-Haenszel Method
By Wen-Chung Wang, Ya-Hui Su. 2004
92 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/f50980a15bb455daf64a9c89af3656546bd521e6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Ching-Lin Shih
- Guo-Wei Sun
- Francis Tuerlinckx
- Wen-Chung Wang
- David Magis
- P. De Boeck
- Carol M. Woods
- Kevin J. Grimm
In Information Systems
In Management Science and Operations Research
- Ching-Lin Shih
- Guo-Wei Sun
- P. De Boeck
- Francis Tuerlinckx
- Wen-Chung Wang
- David Magis
- Carol M. Woods
- Kevin J. Grimm
Citations in the corpus
- Detection of Differential Item Functioning Using the Lasso Approach (2015, background): “As a consequence, one often observes an inflation of the Type I error rates (e.g., Clauser, Mazor, & Hambleton, 1993; Magis & De Boeck, 2012; Wang & Su, 2004).”
- A Review of ETS Differential Item Functioning Assessment Procedures: Flagging Rules, Minimum Sample Size Requirements, and Criterion Refinement (2012, unknown): “(Wang & Su, 2004, made a similar speculation.)”
- The DIF-Free-Then-DIF Strategy for the Assessment of Differential Item Functioning (2012, methodology): “In a series of simulations, Wang and Su (2004a) observed that it was the ASA, rather than the percentage of DIF items, that determines the performances of the Mantel–Haenszel method (Holland & Thayer, 1988) on DIF assessment.”