Nonignorable Consequences of (Partially) Ignoring Missing Item Responses: Students Omit (Constructed Response) Items Due to a Lack of Knowledge

Abstract

In recent literature, alternative models for handling missing item responses in large-scale assessments have been proposed. Based on simulations and arguments based on psychometric test theory, it is argued in this literature that missing item responses should never be scored as incorrect in scaling models but rather treated as ignorable or handled based on a model. The present article shows that these arguments have limited validity and illustrates the consequences in a country comparison using the PIRLS 2011 study. It is argued that students omit (constructed response) items because they do not know the correct item answer. A different treatment of missing item responses than scoring them as incorrect leads to significant changes in country rankings, which induces nonignorable consequences regarding the validity of the results. Additionally, two alternative item response models are proposed based on different assumptions for missing item responses. In the first pseudo-likelihood approach, missing item responses for a particular student are replaced by a score that ranges between zero and a model-implied probability computed based on the non-missing items. In the second approach, the probability of a missing item response is predicted by a latent response propensity variable and the item response itself. The models were applied to the PIRLS 2011 study, demonstrating that country comparisons change under different modeling assumptions for missing item responses.

Keywords

• item response model
• missing item responses
• large-scale assessment
• PIRLS