Recent research has witnessed the expansion of the family of Rasch models. In this talk, I will explicate the expanding Rasch world using ten axes: (1) response category, (2) facet, (3) dimensionality, (4) order, (5) level, (6) growth, (7) latent class, (8) missing data, (9) ranking, and (10) structural equitation modeling. A huge number of Rasch models could be created along these ten axes to tackle many measurement issues. In addition, revisiting those practical issues (e.g., parameter estimation, model-data fit, measurement invariance, adaptive testing, etc.) surrounding the newly created models may be necessary.
|Publication status||Published - Aug 2016|