Statistical Power and Sample Size Requirements for Three Level Hierarchical Cluster Randomized Trials
Article first published online: 11 FEB 2008
© 2008, The International Biometric Society
Volume 64, Issue 4, pages 1256–1262, December 2008
How to Cite
Heo, M. and Leon, A. C. (2008), Statistical Power and Sample Size Requirements for Three Level Hierarchical Cluster Randomized Trials. Biometrics, 64: 1256–1262. doi: 10.1111/j.1541-0420.2008.00993.x
- Issue published online: 24 NOV 2008
- Article first published online: 11 FEB 2008
- Received September 2007. Revised November 2007. Accepted November 2007.
- Effect size;
- Sample size;
- Three level data
Summary Cluster randomized clinical trials (cluster-RCT), where the community entities serve as clusters, often yield data with three hierarchy levels. For example, interventions are randomly assigned to the clusters (level three unit). Health care professionals (level two unit) within the same cluster are trained with the randomly assigned intervention to provide care to subjects (level one unit). In this study, we derived a closed form power function and formulae for sample size determination required to detect an intervention effect on outcomes at the subject's level. In doing so, we used a test statistic based on maximum likelihood estimates from a mixed-effects linear regression model for three level data. A simulation study follows and verifies that theoretical power estimates based on the derived formulae are nearly identical to empirical estimates based on simulated data. Recommendations at the design stage of a cluster-RCT are discussed.