Lasagna Plots: A Saucy Alternative to Spaghetti Plots

Bruce Swihart, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Brian Caffo, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Bryan D. James, Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology
Matthew Strand, Department of Biostatistics, University of Colorado at Denver and Health Sciences Center
Brian S. Schwartz, Johns Hopkins Bloomberg School of Public Health, Division of Occupational and Environmental Health
Naresh M. Punjabi, Department of Medicine, Johns Hopkins University

Abstract

Longitudinal repeated measures data has often been visualized with spaghetti plots for continuous out- comes. For large datasets, this often leads to over-plotting and consequential obscuring of trends in the data. This is primarily due to overlapping of trajectories. Here, we suggest a framework called lasagna plot ting 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. Supplemental material in the form of sample R code additional illustrated examples are available online.