This study investigated the effect of item parameter drift on ability estimates under item response theory. Item response data for two testing occasions were simulated for the two-parameter logistic model under the following crossed conditions: test length, sample size, percentage of drifting items, and type of drift. Results indicated that item parameter drift, under the conditions simulated, had a small effect on ability estimates.
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References
1.
Baker, F. B. (1986). GENIRV: Computer program to generating item responses [Computer program]. Madison: University of Wisconsin, Department of Educational Psychology, Laboratory of Experimental Design.
2.
Baker, F. B. (1990). EQUATE: Computer program for equating two metrics in item response theory [Computer program]. Madison: University of Wisconsin, Laboratory of Experimental Design.
3.
Baker, F. B. (1992). Item response theory. New York: Springer-Verlag.
4.
Bock, R. , Muraki, E., & Pfeiffenberger, W. (1988). Item pool maintenance in the presence of item parameter drift. Journal of Educational Measurement, 25, 275-285.
5.
Chan, K-Y. , Drasgow, F., & Sawin, L. L. (1999). What is the shelf life of a test? The effect of time on psychometrics of a cognitive ability test battery. Journal of Applied Psychology, 84, 610-619.
6.
Cohen, A. S. (1992). Technical manual: University of Wisconsin Placement Testing Program. Madison, WI: Center for Placement Testing.
7.
Cook, L. L. , Eignor, D. R., & Taft, H. L. (1988). A comparative study of the effects of recency of instruction on the stability of IRT and conventional item parameter estimates. Journal of Educational Measurement, 25, 31-45.
8.
Goldstein, H. (1983). Measuring changes in educational attainment over time: Problems and possibilities. Journal of Educational Measurement, 20, 369-377.
9.
Haley, D. C. (1952). Estimation of the dosage mortality relationship when the dose is subject to error (Technical Report No. 15). Stanford, CA: Stanford University, Applied Mathematics and Statistics Laboratory.
10.
Hambleton, R. K. , & Swaminathan, H. (1985). Item response theory: Principles and applications. Boston, MA: Kluwer-Nijhoff.
11.
Hambleton, R. K. , Swaminathan, H., & Rogers, J. (1991). Item response theory. Vol. 2. Hillsdale, NJ: Lawrence Erlbaum.
12.
Lord, F. (1980). Applications of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum.
13.
Mislevy, R. J. (1982, March). Five steps toward controlling item parameter drift. Paper presented at the annual meeting of the American Educational Research Association, New York.
14.
Mislevy, R. J. , & Bock, R. D. (1990). BILOG 3: Item analysis and test scoring with binary logistic models [Computer program]. Mooresville, IN: Scientific Software.
15.
Stocking, M. , & Lord, F. (1983). Developing a common metric in item response theory. Applied Psychological Measurement, 7, 201-210.
16.
Stone, C. A. , & Lane, S. (1991). Use of restricted item response theory models for examining the stability of item parameter estimates over time. Applied Measurement in Education, 4, 125-141.