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• 'Best practices' to analyse bicycle crash causes in correlational studies. • An abbreviated list of crash causation criteria was used. • Risk comparisons between two types of bicycles is the example given. • Controlling for age, gender, and exposure is required to analyse crash risk. The increasing number of bicycle crashes leading to injuries in the Netherlands is frequently related (e.g., in the media) to increased use of the electric bicycle. For this reason, policy makers face the challenge of selecting and implementing the most promising countermeasures including those focused on electric bicycles. It may be questioned, however, to what extent the electric bicycle itself is a (direct) cause of crashes leading to injuries or whether other factors are important for explaining the increased number of bicycle injury crashes. On the basis of an abbreviated list of criteria by Elvik (2011) , this paper illustrates the potential influence of factor inclusions, analysis selections, and data presentations on the general impression about crash causation with the electric bicycle as an example. The aim is to provide a 'best practice guide' by taking into account (1) a theoretical explanation of causal mechanisms, (2) control for confounders, and (3) a statistical association of sufficient strength and consistency in the expected direction. We conclude that an apparent increased risk of electric bicycles may be explained by factors such as age, exposure, health factors, and gender of the cyclist. A relatively simple analysis, by comparing fatality numbers of conventional and electric bicycles, showed that including or excluding these factors may lead to vastly different interpretations of fatality causes and the relative risk of electric bicycles compared to conventional bicycles. [ABSTRACT FROM AUTHOR]