Effects of Anchor Item Methods on the Detection of Differential Item Functioning Within the Family of Rasch Models

Wang, Wen Chung

doi:10.3200/jexe.72.3.221-261

Cited by 84 publications

(163 citation statements)

References 44 publications

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“…It appeared that only when the DIF pattern was balanced would M-ST perform as well as M-SP. This is consistent with the findings in Wang andSu (2004a, 2004b), in which scale purification procedures were implemented onto the M-H, the generalized M-H, and the Mantel methods.…”

Section: Balanced Dif Patternmentioning

confidence: 53%

The MIMIC Method With Scale Purification for Detecting Differential Item Functioning

Wang

Shih

Yang

2009

Educational and Psychological Measurement

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This study implements a scale purification procedure onto the standard MIMIC method for differential item functioning (DIF) detection and assesses its performance through a series of simulations. It is found that the MIMIC method with scale purification (denoted as M-SP) outperforms the standard MIMIC method (denoted as M-ST) in controlling false-positive rates and yielding higher true-positive rates. Only when the DIF pattern is balanced between groups or when there is a small percentage of DIF items in the test does M-ST perform as appropriately as M-SP. Moreover, both methods yield a higher true-positive rate under the two-parameter logistic model than under the three-parameter model. M-SP is preferable to M-ST, because DIF patterns in real tests are unlikely to be perfectly balanced and the percentages of DIF items may not be small.

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Section: Balanced Dif Patternmentioning

confidence: 53%

The MIMIC Method With Scale Purification for Detecting Differential Item Functioning

Wang

Shih

Yang

2009

Educational and Psychological Measurement

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“…We do know that there are less restrictions under the alternative hypothesis, which explains the tendency to conclude that all the items show DIF. This observation is not new (e.g., Hessen, 2005, p. 513) and has enticed researchers to suggest anchoring strategies (e.g., De Boeck, 2008, §7.4;Wang & Yeh, 2003, 2004Stark et al, 2006), and heuristics for iterative purification of the anchor (Lord, 1980, p. 220;Van der Flier, Mellenbergh, Adèr, & Wijn, 1984;Candell & Drasgow, 1988;Wang, Shih, & Sun, 2012). Unfortunately, none of this provides a valid statistical test when there is more than one DIF item.…”

Section: Example 1 (Preservice Teachers)mentioning

confidence: 94%

A Statistical Test for Differential Item Pair Functioning

Bechger

Maris

2014

Psychometrika

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This paper presents an IRT-based statistical test for differential item functioning (DIF). The test is developed for items conforming to the Rasch (Probabilistic models for some intelligence and attainment tests, The Danish Institute of Educational Research, Copenhagen, 1960) model but we will outline its extension to more complex IRT models. Its difference from the existing procedures is that DIF is defined in terms of the relative difficulties of pairs of items and not in terms of the difficulties of individual items. The argument is that the difficulty of an item is not identified from the observations, whereas the relative difficulties are. This leads to a test that is closely related to Lord's (Applications of item response theory to practical testing problems, Erlbaum, Hillsdale, 1980) test for item DIF albeit with a different and more correct interpretation. Illustrations with real and simulated data are provided.

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“…However, Type I error is inflated when the anchor set is contaminated by DIF (Stark et al, 2006;Wang & Yeh, 2003) so it is better to designate anchors. Various strategies for empirically identifying anchors have been applied or suggested (Bolt, Hare, Vitale, & Newman, 2004;Edelen, Thissen, Teresi, Kleinman, & Ocepek-Welikson, 2006;Kim & Cohen, 1995;Rensvold & Cheung, 2001;Stark et al, 2006;Wang, 2004;Woods, in press). Many of them are iterative purification procedures wherein the analysis is repeated several times with apparently differentially functioning items removed one by one.…”

Section: Two-group Irt For Testing Dif: Irt-lr-difmentioning

confidence: 99%

Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis

Woods

2009

Multivariate Behavioral Research

165

201

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Effects of Anchor Item Methods on the Detection of Differential Item Functioning Within the Family of Rasch Models

Cited by 84 publications

References 44 publications

The MIMIC Method With Scale Purification for Detecting Differential Item Functioning

The MIMIC Method With Scale Purification for Detecting Differential Item Functioning

A Statistical Test for Differential Item Pair Functioning

Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis

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