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Pairwise Cluster Randomization

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  • William Rhodes

Abstract

Background: Cluster randomization (CR) is often used for program evaluation when simple random assignment is inappropriate or infeasible. Pairwise cluster random (PCR) assignment is a more efficient alternative, but evaluators seemed to be deterred from PCR because of bias and identification problems. This article explains the problems, argues that they can be mitigated through design choices, and demonstrates that the suitability of PCR can be tested using Monte Carlo procedures. Research Design: The article presents simple formulas showing how the PCR estimator is biased and explains why its standard error is not identified. Formal derivations appear in a longer companion article. Using those formulas, this article discusses how good design can mitigate the problems with bias and identification. Using Monte Carol simulation, this article also shows how to choose between CR and PCR at the design stage. Conclusions: This article advocates for wider use of the PCR design. PCR loses its appeal when the investigator lacks baseline data for matching the clusters. Its use is less compelling when there are a large number of clusters. But when the evaluator is working with a fairly small number of clusters—26 in the running example used in this article—PCR is an attractive alternative to CR.

Suggested Citation

  • William Rhodes, 2014. "Pairwise Cluster Randomization," Evaluation Review, , vol. 38(3), pages 217-250, June.
  • Handle: RePEc:sae:evarev:v:38:y:2014:i:3:p:217-250
    DOI: 10.1177/0193841X14540654
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    References listed on IDEAS

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    1. repec:mpr:mprres:5863 is not listed on IDEAS
    2. Heller, Ruth & Rosenbaum, Paul R. & Small, Dylan S., 2009. "Split Samples and Design Sensitivity in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1090-1101.
    3. Roger Newson, 2002. "Parameters behind "nonparametric" statistics: Kendall's tau,Somers' D and median differences," Stata Journal, StataCorp LP, vol. 2(1), pages 45-64, February.
    4. 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.
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