This study, based on the Rasch model, used R. M. Smith's (1986) classification of measurement disturbances to assess the Rasch model approach to error control and statistical prediction. Partitioning the error component into a person component, an item-person interaction component, and a random unexplained error component has the net effect of reducing the error variance and improving statistical prediction and classification efficiency. The specific goal of this study is to determine the possibility of using the Item and Person Analysis Rasch Model (IPARM) to correct a person's score to eliminate person disturbances. The United States Air Force Placement and Validation Examination was administered to 1,200 freshmen entering the Air Force Academy in Colorado Springs; the French language portion of the test was used. Test data were analyzed using IPARM to identify individual response disturbances and to estimate each person's true score. IPARM can assess item disturbances as well as person disturbances, but this study focused on the latter. Essentially, IPARM uses a person's total score to establish statistical expectancies for each item the individual attempted. Test result correlations with French grades and class rankings indicated that the IPARM-based corrections are useful for improvement of prediction and classification. (TJH)