Extending the cluster approach to differential item functioning in polytomous items

To objectively compare groups on any latent trait using tests, the absence of differential item functioning (DIF) is crucial. While the importance of DIF has been well-established in research, the question of how to identify DIF-free items is still largely open. The fact that item difficulty is not identified from observations may explain this. Recently, DIF tests utilizing the differences between item difficulties across groups, which are identified, were proposed for the Rasch and 2-parameter logistic models. The current paper aims to extend these approaches to the polytomous case using the partial credit model. Performance of the new approach is assessed using a simulation study, and practical recommendations are made.