Longitudinal data, or data that are repeated measurements on various subjects across time, are commonplace in biostatistical studies. The general linear mixed model is a useful statistical tool for analyzing such data and drawing meaningful inferences about them. This paper discusses some of the most common mixed models and fits them to a prototypical example involving repeated measures on blood pressure. Computer implementation is via the MIXED procedure in the SAS System, and code descriptions and output interpretations accompany the example.