Presented at the quarterly meeting of the New York Area SAS Users-Group in December 2008. In virtually any research context, there is likely to be opportunity to apply mixed-models--of which repeated-measures, multilevel, hierarchical and random- and fixed-effect models are specific types-- that improve upon their traditional linear or generalized linear model counterparts. This presentation focused primarily on multi-level modeling and on drawing parallels between the statistical specification of these models and their implementation in SAS. Some time was devoted to the discussion of problems of convergence, some diagnostics and other impediments to the modeling process.