Abstract
This paper describes the appropriateness of Differential Item Functioning (DIF) analysis performed via mixed-effects Rasch models. Groups of subjects with homogeneous Rasch item parameters are found automatically by a model-based partitioning (Rasch tree model). The unifying framework offers the advantage of including the terminal nodes of Rasch tree in the multilevel formulation of Rasch models. In such a way we are able to handle different measurement issues. The approach is illustrated with a cross-national survey on attitude towards female stereotypes. Evidence of groups DIF was detected and presented as well as the estimates of model parameters.
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Sarra, A., Fontanella, L., Di Battista, T., Di Nisio, R. (2013). Interpreting Error Measurement: A Case Study Based on Rasch Tree Approach. In: Giudici, P., Ingrassia, S., Vichi, M. (eds) Statistical Models for Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00032-9_37
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DOI: https://doi.org/10.1007/978-3-319-00032-9_37
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