Design and Analysis of Controlled Trials in Naturally Clustered Environments
Implications for Medical Informatics
- Affiliations of the authors: Columbia University, New York, New York (J-HC, GH, DF); National Yang-Ming University, Taipei, Taiwan (JHC)
- Correspondence and reprints: Jen-Hsiang Chuang, MD, MS, Department of Medical Informatics, Columbia University, 622 West 168th Street, Vanderbilt Clinic, 5th Floor, New York, NY 10032; e-mail: <chuangj{at}dmi.columbia.edu>
- Received 1 August 2001
- Accepted 3 January 2002
Abstract
In medical informatics research, study questions frequently involve individuals who are grouped into clusters. For example, an intervention may be aimed at a clinician (who treats a cluster of patients) with the intention of improving the health of individual patients. Correlation among individuals within a cluster can lead to incorrect estimates of the sample size required to detect an effect and inappropriate estimates of the confidence intervals and the statistical significance of the intervention effects. Contamination, which is the spread of the effect of an intervention or control treatment to the opposite group, often occurs between individuals within clusters. It leads to an attenuation of the effect of the intervention and reduced power to detect a difference. If individuals are randomized in a clinical trial (individual-randomized trial), then correlation must be taken into account in the analysis, and the sample size may need to be increased to compensate for contamination. Randomizing clusters rather than individuals (cluster-randomized trials) can eliminate contamination and may be preferred for logistical reasons. Cluster-randomized trials are generally less efficient than individual-randomized trials, so the tradeoffs must be assessed. Correlation must be taken into account in the analysis and in the sample-size calculations for cluster-randomized trials.
Footnotes
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This work was supported in part by grant R01 LM06910 from the National Library of Medicine and grant R01 HL65365 from the National Institutes of Health. Dr. Chuang was supported in part by the Medical Foundations in Memory of Dr. Chi-Shuen Tsou and Dr. Albery Ly-Young Shen, Taiwan.
