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Interval estimation for response adaptive clinical trials

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  • Tolusso, David
  • Wang, Xikui

Abstract

In this paper we examine a new method for constructing confidence intervals for the difference of success probabilities to analyze dependent data from response adaptive designs with binary responses. Specifically we investigate the feasibility of the Jeffreys-Perks procedure for interval estimation. Simulation results are derived to demonstrate the performance of the Jeffreys-Perks procedure compared with the profile likelihood method. It is found that both asymptotic methods perform well for small sample sizes despite being approximate procedures.

Suggested Citation

  • Tolusso, David & Wang, Xikui, 2011. "Interval estimation for response adaptive clinical trials," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 725-730, January.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:725-730
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    References listed on IDEAS

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    1. Atanu Biswas & Jean–François Angers, 2002. "A Bayesian adaptive design in clinical trials for continuous responses," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 56(4), pages 400-414, November.
    2. Yi Cheng & Donald A. Berry, 2007. "Optimal adaptive randomized designs for clinical trials," Biometrika, Biometrika Trust, vol. 94(3), pages 673-689.
    3. Yi, Yanqing & Wang, Xikui, 2007. "Goodness-of-fit test for response adaptive clinical trials," Statistics & Probability Letters, Elsevier, vol. 77(10), pages 1014-1020, June.
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