Goethals' Guideline for Item Calibration Invariance

The Figure from Kubinger (2005) plots the Rasch item calibrations for 481 males against those for 439 females. Overall, the differences are statistically significant. But Kubinger remarks:

"However, the differences in parameter estimation are of no practical relevance. The differences are too small to impose any systematic handicap on an examinee's test result because the standard error of estimation of the ability parameter is much greater than errors due to the given item parameter differences. Goethals (1994) provided a rule of thumb: Any difference of parameter estimations should not exceed a tenth of the range of the parameters."

Klaus D. Kubinger (2005) Psychological Test Calibration Using the Rasch Model - Some Critical Suggestions on Traditional Approaches. International Journal of Testing, 5:4, 377 - 394

Goethals, R. (1994). Die praktische Erprobung von Alternativen zur multiple-choice-Vorgabe bei Computertests [Experiences with alternatives for traditional multiple-choice response formats in computerized testing]. Unpublished doctoral dissertation, University of Vienna, Austria.




Goethals' Guideline for Item Calibration Invariance … R. Goethals, Rasch Measurement Transactions, 2008, 22:2 p. 1166



Rasch Publications
Rasch Measurement Transactions (free, online) Rasch Measurement research papers (free, online) Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Applying the Rasch Model 3rd. Ed., Bond & Fox Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement Rasch models for measurement, David Andrich Constructing Measures, Mark Wilson Rasch Analysis in the Human Sciences, Boone, Stave, Yale
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