Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research
We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while countries within these groups are still allowed to be heterogeneous. A simulation study is conducted that shows that all parameters can be recovered. We also apply the model to real data on the two components of affective subjective well-being: positive affect and negative affect. The psychometric behavior of these two scales is studied in 28 countries across four continents.
|Keywords||cross-cultural research, differential item functioning, graded response model, hierarchical item response theory, item response theory, latent classes, measurement equivalence, measurement invariance, mixture modeling, multidimensional IRT|
|Persistent URL||dx.doi.org/10.1007/s11336-009-9134-z, hdl.handle.net/1765/16806|
de Jong, M.G., & Steenkamp, J-B.E.M.. (2009). Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research. Psychometrika, 75(1), 3–32. doi:10.1007/s11336-009-9134-z