Comparing completely and stratified randomized designs in cluster randomized trials when the stratifying factor is cluster size: a simulation study.
Stratified randomized designs are popular in cluster randomized trials (CRTs) because they increase the chance of the intervention groups being well balanced in terms of identified prognostic factors at baseline and may increase statistical power. The objective of this paper is to assess the gains in power obtained by stratifying randomization by cluster size, when cluster size is associated with an important cluster level factor which is otherwise unaccounted for in data analysis. A simulation study was carried out using a CRT where UK general practices were the randomized units as a template. The results show that when cluster size is strongly associated with a cluster level factor which is predictive of outcome, the stratified randomized design has superior power results to the completely randomized design and that the superiority is related to the number of clusters.
Lewsey
J D
JD
Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand. jlewsey@rcseng.ac.uk
D016000:Cluster Analysis; D003198:Computer Simulation; D005194:Family Practice; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D018401:Sample Size