Effects of Anchor Item Methods on Differential Item Functioning Detection with the Likelihood Ratio Test

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Factors Influencing the Mantel and Generalized Mantel-Haenszel Methods for the Assessment of Differential Item Functioning in Polytomous Items (2004, unknown): “Zwick, Donoghue and Grima (1993) observed that the Mantel and GMH perform similarly, and both methods are more satisfactory when the studied item is included in the matching criterion than when it is not.”
The Langer-Improved Wald Test for DIF Testing With Multiple Groups (2013, background): “Statistical power to detect uniform and nonuniform DIF increases with increases in sample size, item discrimination, the number of anchors, and the amount of DIF in the data (Ankenmann et al., 1999; Wang & Yeh, 2003; Woods, 2009).”
Testing for Nonuniform Differential Item Functioning With Multiple Indicator Multiple Cause Models (2011, methodology): “…that is able to fit IRT models, but is particularly convenient with Thissen’s (2001) free IRT-LR-DIF software, which has performed well in simulations with binary and ordinal data (Ankenmann, Witt, & Dunbar, 1999; Cohen, Kim, & Wollack, 1996; Kim & Cohen, 1998; Sweeney, 1996; Wang & Yeh, 2003).”
Empirical Selection of Anchors for Tests of Differential Item Functioning (2009, methodology): “These problems may account for the more frequently reported problem of inflated Type I error or false discovery rate (Finch, 2005; Meade & Lautenschlager, 2004; Stark, Chernyshenko, & Drasgow, 2006; Wang, 2004; Wang & Yeh, 2003).”