This chapter discusses some major statistical methods for longitudinal data analysis in biomedical research. We have provided a detailed review to some of the most used statistical models for the analyses of longitudinal data and relevant design issues based on these models. Our focus is on the conceptualization of longitudinal statistical models, the assumptions associated with them, and the interpretations of model parameters. It is not our intention to present the detailed theory on statistical estimations and inferences for these models in this chapter. Instead, we have presented the implementations for some of these basic longitudinal models in SAS through real-world applications.