Methods for Imputing Scores When All Responses Are Missing for One or More Polytomous Items: Accuracy and Impact on Psychometric Property

Though a substantial amount of research exists on imputing missing scores in educational assessments, there is little research on cases where responses or scores to an item are missing for all test takers. In this paper, we tackled the problem of imputing missing scores for tests for which the responses to an item are missing for all test takers. We considered three missing-data imputation methods—the median method, the item response theory (IRT) method, and the two-way method—for imputing scores. We compared the performance of these three imputation methods with respect to their accuracy in estimating scaled scores and test reliability for the aforementioned problem. Real data were used in the comparison. All three methods performed well in imputing scaled scores with negligible imputation error: The IRT method and the median method provided slightly more accurate scaled scores. The two-way method provided the most accurate reliability estimates. Recommendations for practice are provided.