An Empirical Study for the Statistical Adjustment of Rater Bias

Main Article Content

Mustafa İlhan

Abstract

This study investigated the effectiveness of statistical adjustments applied to rater bias in many-facet Rasch analysis. Some changes were first made in the dataset that did not include rater × examinee bias to cause to have rater × examinee bias. Later, bias adjustment was applied to rater bias included in the data file, and the effectiveness of the statistical adjustment was further examined. The outcomes pertaining to the datasets with and without bias, and to which the bias adjustment was applied, were compared. It was concluded that diversities created by rater × examinee bias in examinees’ ability estimation, item difficulty indices and measures of rater severity and leniency were, to a large extent, eliminated by bias adjustment. This result indicates that the bias adjustment using many-facet Rasch analysis is a viable way to control rater bias.

Article Details

How to Cite
İlhan, M. (2019). An Empirical Study for the Statistical Adjustment of Rater Bias. International Journal of Assessment Tools in Education, 6(2), 193-201. Retrieved from http://ijate.net/index.php/ijate/article/view/699
Section
IJATE_Articles

References

Aubin, A. S., St-Onge, C., & Renaud, J. S. (2018). Detecting rater bias using a person-fit statistic: A Monte Carlo simulation study. Perspectives on Medical Education, 7(2), 83–92. http://dx.doi.org/10.1007/s40037-017-0391-8
Bailey, K. (1994). Methods of social research. New York: The Free.
Bennett, R. E. (1991). On the meanings of constructed response. ETS Research Report Series, 2, 1–46. http://dx.doi.org/10.1002/j.2333-8504.1991.tb01429.x
Bennett, R. E., Ward, W. C., Rock, D. A., & LaHart, C. (1990). Toward a framework for constructed response items. ETS Research Report Series, 1, 1–29. http://dx.doi.org/10.1002/j.2333-8504.1990.tb01348.x
Connaway, L. S., & Powell, R. R. (2010). Basic research methods for librarians. Santa Barbara, CA: Libraries Unlimited.
DeMars, C. (2010). Item response theory. Oxford, UK: Oxford University.
Eckes, T. (2005). Examining rater effects in TestDaF writing and speaking performance assessments: A many-facet Rasch analysis. Language Assessment Quarterly, 2(3), 197–221. http://dx.doi.org/10.1207/s15434311laq0203_2
Fahim, M., & Bijani, H. (2011). The effects of rater training on raters’ severity and bias in second language writing assessment. Iranian Journal of Language Testing, 1(1), 1–16. Retrieved from http://www.ijlt.ir/portal/files/401-2011-01-01.pdf
Güler, N., İlhan, M., Güneyli, A., & Demir, S. (2017). An evaluation of the psychometric properties of three different forms of Daly and Miller’s writing apprehension test through Rasch analysis. Educational Sciences: Theory & Practice, 17(3), 721–744. http://dx.doi.org/10.12738/estp.2017.3.0051
Haiyang, S. (2010). An application of classical test theory and many facet Rasch measurement in analyzing the reliability of an English test for non-English major graduates. Chinese Journal of Applied Linguistics, 33(2), 87–102. Retrieved from http://www.celea.org.cn/teic/90/10060807.pdf
Haladyana, T. M. (1997). Writing test items to evaluate higher order thinking. Needham Heights, MA: Allyn & Bacon.
Hogan, T. P., & Murphy, G. (2007) Recommendations for preparing and scoring constructed-response items: What the experts say. Applied Measurement in Education, 20(4), 427–441. http://dx.doi.org/10.1080/08957340701580736
Houston, W. M., Raymond, M.R., & Svec, J. C. (1991). Adjustments for rater effects in performance assessment. Applied Psychological Measurement, 15(4), 409–421. http://dx.doi.org/10.1177/014662169101500411
Hoyt, W. T. (2000). Rater bias in psychological research: When is it a problem and what can we do about it? Psychological Methods, 5(1), 64–86. http://dx.doi.org/10.1037/1082-989X.5.1.64
İlhan, M. (2015). The identification of rater effects on open-ended math questions rated through standard rubrics and rubrics based on the SOLO taxonomy in reference to the many facet Rasch model. Doctoral dissertation, Gaziantep University, Gaziantep, Turkey. Retrieved from https://tez.yok.gov.tr/UlusalTezMerkezi/
İlhan, M. (2016). Comparison of the ability estimations of classical test theory and the many facet Rasch model in measurements with open-ended questions. Hacettepe University Journal of Education, 31(2), 346–368. http://dx.doi.org/10.16986/HUJE.2016015182
Knoch, U., Read, J., & von Randow, J. (2007). Re-training writing raters online: How does it compare with face-to-face training? Assessing Writing, 12(1), 26–43. http://dx.doi.org/10.1016/j.asw.2007.04.001
Kondo Brown, K. (2002). A FACETS analysis of rater bias in measuring Japanese second language writing performance. Language Testing, 19(1), 3–31. https://doi.org/10.1191/0265532202lt218oa
Kumar, DSP D. (2005). Performance appraisal: The importance of rater training. Journal of the Kuala Lumpur Royal Malaysia Police College, 4, 1–15. Retrieved from http://rmpckl.rmp.gov.my/Journal/BI/performanceappraisal.pdf
Lee, M., Peterson, J. J., & Dixon, A. (2010). Rasch calibration of physical activity self-efficacy and social support scale for persons with intellectual disabilities. Research in Developmental Disabilities, 31(4), 903−913. http://dxdoi.org/10.1016/j.ridd.2010.02.010
Linacre, J. M. (2012). Many-facet Rasch measurement: Facets tutorial. Retrieved from http://www.winsteps.com/a/ftutorial2.pdf
Linacre, J. M. (2018). A user's guide to FACETS Rasch-model computer programs. Retrieved from https://www.winsteps.com/manuals.htm
McNamara, J. F., Erlandson, D. A., & McNamara, M. (2013). Measurement and evaluation: Strategies for school improvement. New York, NY: Routledge.
Myford, C. M., & Wolfe, E. W. (2004). Detecting and Measuring rater effects using many-facet Rasch measurement: Part II. Journal of Applıed Measurement, 5(2), 189–227. Retrieved from http://jimelwood.net/students/grips/tables_figures/myford_wolfe_2004.pdf
Nandakumar, R., & Ackerman, T. A. (2004). Test modeling. In D. Kaplan (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 93-105). Thousand Oaks, CA: Sage.
Raymond, M. R., & Houston, W. M. (1990). Detecting and correcting for rater effects inperformance assessment (ACT Research Rep. No. 90-14). Iowa City, American College Testing. Retrieved from http://www.act.org/content/dam/act/unsecured/documents/ACT_RR90-14.pdf
Raymond, M. R., & Viswesvaran, C. (1993). Least squares models to correct for rater effects in performance assessment. Journal of Educational Measurement, 30(3), 253–268. http://dx.doi.org/10.1111/j.1745-3984.1993.tb00426.x
Saal, F. E., Downey, R. G., & Lahey, M. A. (1980). Rating the ratings: Assessing the psychometric quality of rating data. Psychological Bulletin, 88(2), 413–428. http://dx.doi.org/10.1037/0033-2909.88.2.413
Wright, B. D., & Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8(3), 370–371. Retrieved from https://www.rasch.org/rmt/rmt83b.htm