Item response theory models are often applied when a number items are used to measurea unidimensional latent variable. Originally proposed and used within educationalresearch, they are also used when focus is on physical functioning or psychological wellbeing.Modern applications often need more general models, typically models for multidimensionallatent variables or longitudinal models for repeated measurements. This paperdescribes a SAS macro that fits two-dimensional polytomous Rasch models using a specifi-cation of the model that is sufficiently flexible to accommodate longitudinal Rasch models.The macro estimates item parameters using marginal maximum likelihood estimation. Agraphical presentation of item characteristic curves is included.