Abstract
Longitudinal repeated-measures data often have been visualized with spaghetti plots for continuous outcomes. For large datasets, the use of spaghetti plots often leads to the over-plotting and consequential obscuring of trends in the data. This obscuring of trends is primarily due to the overlapping of trajectories. Here, we suggest a framework called lasagna plotting that constrains the subject-specific trajectories to prevent overlapping and utilizes gradients of color to depict the outcome. Dynamic sorting and visualization is demonstrated as an exploratory data analysis tool.