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Power Analysis of Cutoff-Based Randomized Clinical Trials

Author

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  • Joseph C. Cappelleri

    (New England Medical Center)

  • Richard B. Darlington

    (Cornell University)

  • William M.K. Trochim

    (Cornell University)

Abstract

A cutoff-based randomized clinical trial couples cutoff-based assignment on an appropriate covariate with random assignment to help balance ethical and scientific concerns in certain situations. A statistical power algorithm based on the Fisher Z method is developed that is particular to and inclusive of cutoff-based random clinical trials and the single cutoff-point (regression-discontinuity) design, which has no randomization. This article quantifies power and sample size estimates for varying levels of randomization and cutoff-based assignment. Although more randomization engenders greater statistical power, less randomization requires a much larger increase in sample size for small treatment effects.

Suggested Citation

  • Joseph C. Cappelleri & Richard B. Darlington & William M.K. Trochim, 1994. "Power Analysis of Cutoff-Based Randomized Clinical Trials," Evaluation Review, , vol. 18(2), pages 141-152, April.
    • Handle: RePEc:sae:evarev:v:18:y:1994:i:2:p:141-152
    DOI: 10.1177/0193841X9401800202
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    References listed on IDEAS

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    1. Joseph C. Cappelleri & William M.K. Trochim & T.D. Stanley & Charles S. Reichardt, 1991. "Random Measurement Error Does Not Bias the Treatment Effect Estimate in the Regression-Discontinuity Design," Evaluation Review, , vol. 15(4), pages 395-419, August.
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    Cited by:

    1. Ceri Wilson & Jenny Secker, 2015. "Validation of the Social Inclusion Scale with Students," Social Inclusion, Cogitatio Press, vol. 3(4), pages 52-62.

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