Longitudinal data arise when repeated measurements are taken on the same individuals over time. Inference about between-group differences of within-subject change is usually of interest. This statistical primer for cardiothoracic and vascular surgeons aims to provide a short and practical introduction of biostatistical methods on how to analyse repeated-measures data. Several methodological approaches for analysing repeated measures will be introduced, ranging from simple approaches to advanced regression modelling. Design considerations of studies involving repeated measures are discussed, and the methods are illustrated with a data set measuring coronary sinus potassium in dogs after occlusion. Cardiothoracic and vascular surgeons should be aware of the myriad approaches available to them for analysing repeated-measures data, including the relative merits and disadvantages of each. It is important to present effective graphical displays of the data and to avoid arbitrary cross-sectional statistical comparisons.