ABSTRACT
This chapter focuses on using the multilevel modeling framework to analyze longitudinal data. Longitudinal data occurs when a series of measurements are made on each individual in the sample, usually over some period of time. Although there are alternatives to this temporal definition of longitudinal data (e.g., measurements made at multiple locations within a plot of land), the focus is on the most common type of longitudinal, which is time based. The chapter demonstrates the application to a special case of tools that was already discovered. It concludes by describing the advantages of using multilevel models with longitudinal data. The key to this analysis is the treatment of each measurement in time as a level 1 data point and the individuals on whom the measurements are made as level 2. The chapter shows that the multilevel modeling tools studied together in through can be applied in the context of longitudinal data.
