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Modeling Nonignorable Missing Data With Item Response Theory (IRT) IRT

Rose, Norman; von Davier, Matthias; Xu, Xueli
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Item Response Theory (IRT), Multidimensional Item Response Theory (MIRT), Missing Data, Large-Scale Assessment, Latent Regression


In this project, we analyzed the effects of treating omitted responses either as missing or as wrong, as is done in the majority of international studies, and compared these data-treatment solutions to model-based approaches to treating omitted responses. The two types of model-based approaches used in this study are: (a) extensions of multidimensional item response theory (IRT) with an additional dimension based on response indicator variables defined and calibrated together with the set of items containing the observed responses and (b) multidimensional, multiple-group IRT models with a grouping variable representing the within-country stratification of respondents by the amount of omitted responses. These two model-based approaches were compared on the basis of simulated data and data from about 250,000 students from 30 Organisation for Economic Co-operation and Development (OECD) Member countries participating in an international large-scale assessment.

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