Detection of differential item functioning magnitude in psychological measurements with missing data

Authors

  • Alexander Oluwafemi Obafemi Awolowo University
  • Femi Timothy Adekunle
  • Eyitayo Rufus Ifedayo AFOLABI

Keywords:

full information maximum likelihood, multiple imputation, differential item functioning, achievement motivation inventory

Abstract

Abstract

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References

Awuor, R. A. (2008). Effect of Unequal Sample Sizes on the Power of DIF Detection: An IRT Based Monte Carlo Study with SIBTEST and Mantel-Haenszel Procedures. Unpublished Ph.D Dissertation submitted to the faculty of the Virginia Polytechnic Institute and State University.

Baraldi N. A., & Enders, C.K. (2009).An introduction to modern missing data analyses. Journal of School Psychology 48 (2010) 5–37

Garrett, P. L. (2009). "A Monte Carlo Study Investigating Missing Data, Differential Item Functioning, and Effect Size." Dissertation, Georgia State University, 2009. https://scholarworks.gsu.edu/eps_diss/35

Kilmen, S. (2016). Effect of DIF Magnitudes, Focal Group Sample Size, and DIF Ratio on the Performance of SIBTEST. International J. Soc. Sci. & Education 2016 Vol.6 Issue 1, ISSN: 2223- 4934 E and 2227-393X Print

Monahan, Mchorney, Stump and Perkins (2007). Odds Ratio, Delta, ETS Classification, and Standardization Measures of DIF Magnitude for Binary Logistic Regression. Journal of Educational and Behavioral Statistics Vol. 32, No. 1, pp. 92–109 DOI: 10.3102/107699860629803-AERA and ASA. http://jebs.aera.net

Muthee, J. M. & Thomas, I. (2009). Predictors of Achievement Motivation Among Kenyan Adolescents the Psyche space Vol. 3, No. 2, 39-44, July 2009.

Orley, G. J., Multiple Imputation of the Guessing Parameter in the Case of Missing Data (2017). Public Access Theses and Dissertations from the College of Education and Human Sciences. 288. Retrieved from http://digitalcommons.unl.edu/cehsdiss/288

Robitzsch, A., & Rupp, A. A. (2009). Impact of missing data on the detection of differential item functioning: The case of Mantel-Haenszel and logistic regression analysis. Educational and Psychological Measurement, 69(1), 18-34.

Rodriguez De Gil, P. (2015). An Empirical Comparison of the Effect of Missing Data on Type I Error and Statistical Power of the Likelihood Ratio Test for Differential Item Functioning: An Item Response Theory Approach using the Graded Response Model. An unpublished Ph.D Thesis of the University of South Florida

Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147-177

Thissen, D., Steinberg, L., & Wainer, H. (1993). Detection of differential item functioning using the parameters of item response models.In P. W. Holland, & H. Wainer (Eds.). Differential item functioning, (pp. 130-215). Hillsdale, England: Lawrence Erlbaum Associates, Inc.

Zwick, R. (2012). A Review of ETS Differential Item Functioning Assessment Procedures: Flagging Rules, Minimum Sample Size Requirements, and Criterion Refinement. Retrieved from http://www.ets.org/research/contact.html, June 14, 2020

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Published

2022-06-27

How to Cite

Oluwafemi, A., Adekunle, F. T., & AFOLABI, E. R. I. (2022). Detection of differential item functioning magnitude in psychological measurements with missing data. Journal of Computer Adaptive Testing in Africa, 1, 27–35. Retrieved from https://jocatia.acata.org/index.php/jocatia/article/view/16

Issue

Vol. 1 (2022): Journal of Computer Adaptive Testing in Africa

Section

Articles (CAT)

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Copyright (c) 2024 Alexander Oluwafemi, Femi Timothy Adekunle, Eyitayo Rufus Ifedayo AFOLABI

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