  Longitudinal (panel) data provide the opportunity to examine temporal
patterns of individuals, because measurements are collected on the same person
at different, and often irregular, time points. The data is typically
visualised using a "spaghetti plot", where a line plot is drawn for each
individual. When overlaid in one plot, it can have the appearance of a bowl of
spaghetti. With even a small number of subjects, these plots are too overloaded
to be read easily. The interesting aspects of individual differences are lost
in the noise. Longitudinal data is often modelled with a hierarchical linear
model to capture the overall trends, and variation among individuals, while
accounting for various levels of dependence. However, these models can be
difficult to fit, and can miss unusual individual patterns. Better visual tools
can help to diagnose longitudinal models, and better capture the individual
experiences. This paper introduces the R package, brolgar (BRowse over
Longitudinal data Graphically and Analytically in R), which provides tools to
identify and summarise interesting individual patterns in longitudinal data.
