Abstract
In response to the target article by Teresi et al. (2021), we explain why the article is useful and we also present a different approach. An alternative category of differential item functioning (DIF) is presented with a corresponding way of modeling DIF, based on random person and random item effects and explanatory covariates.
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References
Ackerman, T. A. (1992). A didactic explanation of item bias, item impact, and item validity from a multidimensional perspective. Journal of Educational Measurement, 29, 67–91. https://doi.org/10.1111/j.1745-3984.1992.tb00368.x.
Bauer, D. J., Belzak, W. C. M., & Cole, V. T. (2020). Simplifying the assessment of measurement invariance over multiple background variables: Using regularized moderated nonlinear factor analysis to detect differential item functioning. Structural Equation Modeling: A Multidisciplinary Journal, 27, 43–55. https://doi.org/10.1080/10705511.2019.1642754.
Bechger, T. M., & Maris, G. (2015). A statistical test for differential item pair functioning. Psychometrika, 80, 317–340. https://doi.org/10.1007/s11336-014-9408-y.
Cheng, C.-P., Chen, C.-C., Shin, C.-L. (2020).An exploratory strategy to identify and define sources of differential item functioning. Applied Psychological Measurement, 44, 548-560. https://doi.org/10.1177/0146621620931190.
Cho, S.-J., Partchev, I., & De Boeck, P. (2012). Parameter estimation of multiple item profiles models. British Journal of Mathematical and Statistical Psychology, 65, 438–466. https://doi.org/10.1111/j.2044-8317.2011.02036.x.
Cho, S.-J., Suh, Y., & Lee, W.-Y. (2016a). After DIF items are detected: IRT calibration and scoring in the presence of DIF. Applied Psychological Measurement, 40, 573–591. https://doi.org/10.1177/0146621616664304.
Cho, S.-J., Suh, Y., & Lee, W.-Y. (2016b). An NCME instructional module on latent DIF analysis using mixture item response models. Educational Measurement: Issues and Practice, 35, 48–61.
De Boeck, P. (2008). Random item IRT models. Psychometrika, 73, 533–559. https://doi.org/10.1007/s11336-008-9092-x.
De Boeck, P., Cho, S.-J., & Wilson, M. (2011). Explanatory secondary dimension modeling of latent differential item functioning. Applied Psychological Measurement, 35, 583–603. https://doi.org/10.1177/0146621611428446.
De Boeck, P., & Wilson, M. (Eds.). (2004). Explanatory item response models: A generalized linear and nonlinear approach. New York: Springer.
Magis, D., & De Boeck, P. (2011). A robust outlier approach to prevent Type 1 error inflation in DIF. Educational and Psychological Measurement, 72, 291–311. https://doi.org/10.1177/0013164411416975.
Magis, D., Tuerlinckx, F., & De Boeck, P. (2015). Detection of differential item functioning using the Lasso approach. Journal of Educational and Behavioral Statistics, 40, 111–135. https://doi.org/10.3102/1076998614559747.
Shealy, R. T., & Stout, W. F. (1993). An item response theory model for test bias and differential test functioning. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 197–239). Hillsdale: Lawrence Erlbaum.
Teresi, J. A., Wang, C., Kleinman, M., Jones, B. N., & Weiss, D. J. (2021). Differential item functioning analyses of the patient reported outcomes measurement information system (PROMIS) measures: Methods, challenges, advances, and future directions. Psychometrika.
Tutz, G., & Schauberger, G. (2015). A penalty approach to differential item functioning in Rasch models. Psychometrika, 80, 21–43. https://doi.org/10.1007/s11336-013-9377-6.
Van den Noortgate, W., & De Boeck, P. (2005). Assessing and explaining differential item functioning using logistic mixed models. Journal of Educational and Behavioral Statistics, 30, 443–464. https://doi.org/10.3102/10769986030004443.
Verhagen, A. J., & Fox, J. P. (2013). Bayesian tests of measurement invariance. British Journal of Mathematical and Statistical Psychology, 66, 383–401.
Wainer, H. (2010). 14 conversations about three things. Journal of Educational and Behavioral Statistics, 35, 5–25. https://doi.org/10.3102/1076998609355124.
Wang, W.-C. (2004). Effects of anchor item methods on the detection of differential item functioning within the family of Rasch models. Journal of Experimental Education, 72, 221–261. https://doi.org/10.3200/JEXE.72.3.221-261.
Yuan, K.-H., Liu, H., & Han, Y. (2021). Differential item functioning analysis without a priori information on anchor items: QQ plots and graphical test. Psychometrika. https://doi.org/10.1007/s11336-021-09746-5.
Zumbo, B. D. (2007). Three generations of DIF analyses: Considering where it has been, where it is now, and where it is going. Language Assessment Quarterly, 4, 223–233. https://doi.org/10.1080/15434300701375832.
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De Boeck, P., Cho, SJ. Not all DIF is shaped similarly. Psychometrika 86, 712–716 (2021). https://doi.org/10.1007/s11336-021-09772-3
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DOI: https://doi.org/10.1007/s11336-021-09772-3