Effect of imbalance and intracluster correlation coefficient in cluster randomization trials with binary outcomes...

In some cluster randomization trials, the number of clusters cannot exceed a specified maximum value due to cost constraints or other practical reasons. Donner and Klar [Donner A, and Klar N. Design and analysis of cluster randomization trials in health research. Oxford University Press 2000] provided the sample size formula for the number of subjects required per cluster when the number of clusters cannot exceed a specified maximum value. The sample size formula of Donner and Klar assumes that the number of subjects is the same in each cluster. In practical situations, the number of subjects may be different among clusters. We conducted simulation studies to investigate the effect of the cluster size variability (kappa) and the intracluster correlation coefficient (rho) on the power of the study in which the number of available clusters is fixed in advance. For the balanced case (kappa=1.0), i.e., equal cluster size among clusters, the sample size formula yielded empirical powers close to the nominal level even when the number of available clusters per group (k*) is as small as 10. The sample size formula yielded empirical powers close to the nominal level when the number of available clusters per group (k*) is at least 20 and the imbalance parameter (kappa) is at least 0.8. Empirical powers were close to the nominal level when (rho< or =0.02, kappa> or =0.8, and k*=10) or (rho< or =0.02, kappa=0.8, and k*=20).