Vanhove, Jan 2020-08-31 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. application/pdf https://folia.unifr.ch/global/documents/308755 https://folia.unifr.ch/documents/308755/files/vanhove2020_cluster_covariates.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.31234/osf.io/ef4zc info:eu-repo/semantics/openAccess License undefined PyArXiv. - 2020, p. 1-45 cluster randomisation covariates experimental design power Type-I error simulation info:eu-repo/classification/udc/81 Capitalising on covariates in cluster-randomised experiments http://purl.org/coar/resource_type/c_6501