An analysis of test data including a multiple-choice multiple-answer item using the nominal categories model

Abstract

In this research, test data including a multiple-choice multiple-answer item were analysed using the nominal categories model. The results revealed that response probabilities for the answer to each item are described as a function on a latent trait scale. Further, the result shows that some of the items are composed of attractive distracter choices. We have also found that the nominal categories model is useful not only for multiple-choice items but also for multiple-choice multiple-answer items. In addition to the analysis using the nominal categories model, we also obtained results from the analysis on multiple choice-multiple-answer items using a binary response model. We then compared both these results. According to the results, using the nominal categories model to analyse this type of item yielded the largest information.