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Relative risk estimated from the ratio of two median unbiased estimates

Author

Listed:
  • Rickey E. Carter
  • Yan Lin
  • Stuart R. Lipsitz
  • Robert G. Newcombe
  • Kathie L. Hermayer

Abstract

Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach. Copyright (c) 2010 Royal Statistical Society.

Suggested Citation

  • Rickey E. Carter & Yan Lin & Stuart R. Lipsitz & Robert G. Newcombe & Kathie L. Hermayer, 2010. "Relative risk estimated from the ratio of two median unbiased estimates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(4), pages 657-671.
  • Handle: RePEc:bla:jorssc:v:59:y:2010:i:4:p:657-671
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    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9876.2010.00711.x
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    1. Alan Agresti & Yongyi Min, 2001. "On Small-Sample Confidence Intervals for Parameters in Discrete Distributions," Biometrics, The International Biometric Society, vol. 57(3), pages 963-971, September.
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