Although Rasch models have been shown to be a sound methodological approach to develop and validate measures of psychological constructs for more than 50 years, they remain underutilized in psychology and other social sciences. Until recently, one reason for this underutilization was the lack of syntactically simple procedures to fit Rasch and item response theory (IRT) models in general statistical software packages. In this article, the authors demonstrate how to fit the standard dichotomous Rasch model and a dichotomous one-parameter logistic IRT model with nested random effects via the easy-to-use GLIMMIX procedure in SAS 9.3. For comparison purposes, the standard dichotomous Rasch model was also fit using the Rasch specialized software, WINSTEPS 3.68.2. The SAS code used to simulate the data on which the Rasch model was fit is provided to allow replication of estimates. Findings suggest that the GLIMMIX procedure may be a viable option for fitting the standard dichotomous Rasch and dichotomous IRT models. (Contains 5 figures, 2 tables, and 3 notes.)