Capitalising on covariates in cluster-randomised experiments

In cluster-randomised experiments, participants are randomly assigned to the conditions not on an individual basis but in entire groups. For instance, all pupils in a class are assigned to the same condition. This article reports on a series of simulations that were run to determine (1) how the clusters (e.g., classes) in such experiments should be assigned to the conditions if a relevant covariate is available at the outset of the study (e.g., a pretest) and (2) how the data the study produces should be analysed if researchers want to maximise their statistical power while retaining nominal Type-I error rates. The R code used for the simulation is freely accessible online, allowing researchers who need to plan and analyse a cluster- randomised experiment to tailor the simulation to the specifics of their study and determine which approach is likely to work best