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Pitfalls of and Controversies in Cluster Randomization Trials

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  • Donner, A.
  • Klar, N.

Abstract

It is now well known that standard statistical procedures become invalidated when applied to cluster randomized trials in which the unit of inference is the individual. A resulting consequence is that researchers conducting such trials are faced with a multitude of design choices, including selection of the primary unit of inference, the degree to which clusters should be matched or stratified by prognostic factors at baseline, and decisions related to cluster subsampling. Moreover, application of ethical principles developed for individually randomized trials may also require modification. We discuss several topics related to these issues, with emphasis on the choices that must be made in the planning stages of a trial and on some potential pitfalls to be avoided.

Suggested Citation

  • Donner, A. & Klar, N., 2004. "Pitfalls of and Controversies in Cluster Randomization Trials," American Journal of Public Health, American Public Health Association, vol. 94(3), pages 416-422.
    • Handle: RePEc:aph:ajpbhl:2004:94:3:416-422_2
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    Citations

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    Cited by:

    1. Frédéric Douville & Gaston Godin & France Légaré & Marc Germain, 2014. "Implementation Intentions as a Strategy to Increase the Notification Rate of Potential Ocular Tissue Donors by Nurses: A Clustered Randomized Trial in Hospital Settings," Nursing Research and Practice, Hindawi, vol. 2014, pages 1-7, July.
    2. Sophie Song and Katsushi S. Imai, 2018. "Does the Hunger Safety Net Programme Reduce Multidimensional Poverty? Evidence from Kenya," OPHI Working Papers ophiwp124.pdf, Queen Elizabeth House, University of Oxford.
    3. Stefanie Behncke, 2012. "How Do Shocks to Non-Cognitive Skills Affect Test Scores?," Annals of Economics and Statistics, GENES, issue 107-108, pages 155-173.
    4. Moonseong Heo & Andrew C. Leon, 2008. "Statistical Power and Sample Size Requirements for Three Level Hierarchical Cluster Randomized Trials," Biometrics, The International Biometric Society, vol. 64(4), pages 1256-1262, December.
    5. Vivek F. Farias & Andrew A. Li & Tianyi Peng & Andrew Zheng, 2022. "Markovian Interference in Experiments," Papers 2206.02371, arXiv.org, revised Jun 2022.
    6. William Rhodes, 2014. "Pairwise Cluster Randomization," Evaluation Review, , vol. 38(3), pages 217-250, June.
    7. Mira Bierbaum & Eleonora E M Nillesen, 2021. "Sustaining the integrity of the threatened self: A cluster-randomised trial among social assistance applicants in the Netherlands," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-21, June.
    8. Benjamin F. Arnold & Francois Rerolle & Christine Tedijanto & Sammy M. Njenga & Mahbubur Rahman & Ayse Ercumen & Andrew Mertens & Amy J. Pickering & Audrie Lin & Charles D. Arnold & Kishor Das & Chris, 2024. "Geographic pair matching in large-scale cluster randomized trials," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    9. Keenan A. Pituch & Laura M. Stapleton, 2012. "Distinguishing Between Cross- and Cluster-Level Mediation Processes in the Cluster Randomized Trial," Sociological Methods & Research, , vol. 41(4), pages 630-670, November.

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