Implications of Removing Random Guessing from Rasch Item Estimates in Vertical Scaling

Large scale testing programs often involve a number of assessments that include multiple choice items administered to students in different grades. The Rasch model is sometimes used to transform the raw test scores onto a common vertical scale of proficiency. However, with multiple choice items students may guess and the Rasch model makes no provision for guessing. In this study a procedure for removing random guessing from Rasch item estimates is applied to two assessments. The results showed that, when there was guessing, the vertical scale of proficiency was shrunk. Moreover, the highly proficient students were penalised more than the low proficiency students were advantaged by guessing. After removing the effect of guessing from the estimates, the vertical scale was more spread out. Also, because proficient students answer the more difficult items correctly at a greater rate than the less proficient students, they obtained the greatest benefit when the effect of guessing had been removed from the estimates of these items.