Existing methods to analyse data from repeated arteriographic progression/regression studies are restrictive and do not fully explore the dynamics of coronary artherosclerosis. We present a new approach making a distinction between new occlusions, new lesions, and growth of existing lesions. Random effect models, based on the logistic, the Poisson, and the normal distribution are proposed with correlation depending on distance. The data from the Regression Growth Evaluation Statin Study (REGRESS) are used to validate the model. Lipid lowering treatment of pravastatin resulted in less growth of existing lesions and fewer new lesions than when placebo was given. Fewer new lesions were found in segments influenced by percutaneous transluminal coronary angioplasty (PTCA) than in segments not influenced by PTCA. Similarly, the growth of lesions influenced by PTCA was smaller than lesions not influenced by PTCA. More new occlusions were found in segments influenced by coronary arterial bypass grafting (CABG) than in segments not influenced by CABG, but 98 per cent of the new occlusions were located proximal to the bypass anastomosis. Similarly, existing lesions proximal to the bypass anastomosis showed larger growth (p < 0.001). We conclude that our new approach for analysing the arteriographic data from repeated coronary arteriographic studies appeared a fruitful way to analyse the dynamics of coronary atherosclerosis.