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Accounting for cluster randomization: A review of primary prevention trials, 1990 through 1993

Author

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  • Simpson, J.M.
  • Klar, N.
  • Donner, A.

Abstract

Objectives. This methodological review aims to determine the extent to which design and analysis aspects of cluster randomization have been appropriately dealt with in reports of primary prevention trials. Methods. All reports of primary prevention trials using cluster randomization that were published from 1990 to 1993 in the American Journal of Public Health and Preventive Medicine were identified. Each article was examined to determine whether cluster randomization was taken into account in the design and statistical analysis. Results. Of the 21 articles, only 4 (19%) included sample size calculations or discussions of power that allowed for clustering, while 12 (57%) took clustering into account in the statistical analysis. Conclusions. Design and analysis issues associated with cluster randomization are not recognized widely enough. Reports of cluster randomized trials should include sample size calculations and statistical analyses that take clustering into account, estimates of design effects to help others planning trials, and a table showing the baseline distribution of important characteristics by intervention group, including the number of clusters and average cluster size for each group.

Suggested Citation

  • Simpson, J.M. & Klar, N. & Donner, A., 1995. "Accounting for cluster randomization: A review of primary prevention trials, 1990 through 1993," American Journal of Public Health, American Public Health Association, vol. 85(10), pages 1378-1383.
    • Handle: RePEc:aph:ajpbhl:1995:85:10:1378-1383_5
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    Cited by:

    1. Jonathan L. Blitstein & Peter J. Hannan & David M. Murray & William R. Shadish, 2005. "Increasing the Degrees of Freedom in Existing Group Randomized Trials," Evaluation Review, , vol. 29(3), pages 241-267, June.
    2. Henry A. Feldman & Sonja M. McKinlay & Minoo Niknian, 1996. "Batch Sampling To Improve Power in a Community Trial," Evaluation Review, , vol. 20(3), pages 244-274, June.
    3. Paul J. Gruenewald, 1997. "Analysis Approaches To Community Evaluation," Evaluation Review, , vol. 21(2), pages 209-230, April.
    4. S. Mukhopadhyay & S. W. Looney, 2009. "Quantile dispersion graphs to compare the efficiencies of cluster randomized designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1293-1305.
    5. Ahn, Chul & Hu, Fan & Skinner, Celette Sugg, 2009. "Effect of imbalance and intracluster correlation coefficient in cluster randomized trials with binary outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 596-602, January.
    6. Sherri P. Varnell & David M. Murray & William L. Baker, 2001. "An Evaluation of Analysis Options for the One-Group-Per-Condition Design," Evaluation Review, , vol. 25(4), pages 440-453, August.

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