Öz
Differential item functioning (DIF) indicates
existence of items in a test on which different groups of examinees perform
differentially. The groups in DIF analyses are typically designated based on
their manifest characteristics such as gender and ethnicity. Previous research
showed that, examinees of a manifest group may not be homogeneous on the
dimension that is actually causing DIF. That is, the manifest groups have a
weak relationship with the latent groups that explicit true differential
performance on items. In this study, DIF items on the basis of gender were
identified for PISA 2012 mathematics data from Turkish subsample. Then, latent
groups in the subsample were estimated in order to detect the true groups that
perform differentially.
Anahtar Kelimeler
Differential item functioning DIF item response theory IRT likelihood ratio test manifest DIF latent DIF
Kaynakça
- 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. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723. Cho, S.-J., Suh, Y., & Lee, W.-y. (2016). An NCME instructional module on latent DIF analysis using mixture item response models. Educational Measurement: Issues and Practice, 35, 48-61. Dorans, N. J., & Holland, P. W. (1993). DIF detection and description: Mantel-Haenzel and standardization. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 35-66). Hillsdale, NJ: Erlbaum. Holland, P. W., & Wainer, H. (1993). Differential item functioning. Hillsdale, NJ: Erlbaum. Ip, E. H. (2010). Empirically indistinguishable multidimensional IRT and locally dependent unidimensional item response models. British Journal of Mathematical and Statistical Psychology, 63, 395-416. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores (with contributions by A. Birnbaum). Reading, MA: Addison-Wesley. Lunn, D., Spiegelhalter, D., Thomas, A., & Best, N. (2009). The BUGS project: Evolution, critique and future directions. Statistics in medicine, 28, 3049-3082. McDonald, R. P. (1999). Test theory: A unified approach. Mahwah, NJ: Erlbaum. OECD. (2014), PISA 2012 Technical Report. Retrieved October 1, 2017, from https://www.oecd.org/pisa/pisaproducts/PISA-2012-technical-report-final.pdf Reckase, M. D. (1979). Unifactor latent trait models applied to multifactor tests: Results and implications. Journal of Educational Statistics, 4, 207-230. Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling a bifactor perspective. Educational and Psychological Measurement, 73, 5-26. Samuelsen, K. M. (2005). Examining differential item functioning from a latent class perspective. Unpublished doctoral dissertation, University of Maryland, College Park. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464. Steinberg, L., & Thissen, D. (1996). Uses of item response theory and the testlet concept in the measurement of psychopathology. Psychological Methods, 1, 81-97. Thissen, D. (2001). Software for the computation of the statistics involved in item response theory likelihood-ratio tests for differential item functioning [Computer software]. Chapel Hill: University of North Carolina at Chapel Hill. Thissen, D., Steinberg, L., & Gerrard, M. (1986). Beyond group-mean differences: The concept of item bias. Psychological Bulletin, 99, 118-128. 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. 67-113). Hillsdale, NJ: Erlbaum. Zwick, R. (2012). A review of ETS differential item functioning assessment procedures: Flagging rules, minimum sample size requirements, and criterion refinement (Research Report. No. RR-12-08). Princeton, NJ: Educational Testing Service.
Öz
Kaynakça
- 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. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723. Cho, S.-J., Suh, Y., & Lee, W.-y. (2016). An NCME instructional module on latent DIF analysis using mixture item response models. Educational Measurement: Issues and Practice, 35, 48-61. Dorans, N. J., & Holland, P. W. (1993). DIF detection and description: Mantel-Haenzel and standardization. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 35-66). Hillsdale, NJ: Erlbaum. Holland, P. W., & Wainer, H. (1993). Differential item functioning. Hillsdale, NJ: Erlbaum. Ip, E. H. (2010). Empirically indistinguishable multidimensional IRT and locally dependent unidimensional item response models. British Journal of Mathematical and Statistical Psychology, 63, 395-416. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores (with contributions by A. Birnbaum). Reading, MA: Addison-Wesley. Lunn, D., Spiegelhalter, D., Thomas, A., & Best, N. (2009). The BUGS project: Evolution, critique and future directions. Statistics in medicine, 28, 3049-3082. McDonald, R. P. (1999). Test theory: A unified approach. Mahwah, NJ: Erlbaum. OECD. (2014), PISA 2012 Technical Report. Retrieved October 1, 2017, from https://www.oecd.org/pisa/pisaproducts/PISA-2012-technical-report-final.pdf Reckase, M. D. (1979). Unifactor latent trait models applied to multifactor tests: Results and implications. Journal of Educational Statistics, 4, 207-230. Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling a bifactor perspective. Educational and Psychological Measurement, 73, 5-26. Samuelsen, K. M. (2005). Examining differential item functioning from a latent class perspective. Unpublished doctoral dissertation, University of Maryland, College Park. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464. Steinberg, L., & Thissen, D. (1996). Uses of item response theory and the testlet concept in the measurement of psychopathology. Psychological Methods, 1, 81-97. Thissen, D. (2001). Software for the computation of the statistics involved in item response theory likelihood-ratio tests for differential item functioning [Computer software]. Chapel Hill: University of North Carolina at Chapel Hill. Thissen, D., Steinberg, L., & Gerrard, M. (1986). Beyond group-mean differences: The concept of item bias. Psychological Bulletin, 99, 118-128. 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. 67-113). Hillsdale, NJ: Erlbaum. Zwick, R. (2012). A review of ETS differential item functioning assessment procedures: Flagging rules, minimum sample size requirements, and criterion refinement (Research Report. No. RR-12-08). Princeton, NJ: Educational Testing Service.
Ayrıntılar
| Bölüm | Articles |
|---|---|
| Yazarlar | |
| Yayımlanma Tarihi | 10 Aralık 2017 |
| Yayımlandığı Sayı | Yıl 2017 Cilt: 8 |
- Makale Dosyaları
