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Adaptive and nonadaptive group sequential tests

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  • Christopher Jennison
  • Bruce W. Turnbull

Abstract

Methods have been proposed for redesigning a clinical trial at an interim stage in order to increase power. In order to preserve the type I error rate, methods for unplanned design-change have to be defined in terms of nonsufficient statistics, and this calls into question their efficiency and the credibility of conclusions reached. We evaluate schemes for adaptive redesign, extending the theoretical arguments for use of sufficient statistics of Tsiatis & Mehta (2003) and assessing the possible benefits of preplanned adaptive designs by numerical computation of optimal tests; these optimal adaptive designs are concrete examples of optimal sequentially planned sequential tests proposed by Schmitz (1993). We conclude that the flexibility of unplanned adaptive designs comes at a price and we recommend that the appropriate power for a study should be determined as thoroughly as possible at the outset. Then, standard error-spending tests, possibly with unevenly spaced analyses, provide efficient designs, but it is still possible to fall back on flexible methods for redesign should study objective change unexpectedly once the trial is under way. Copyright 2006, Oxford University Press.

Suggested Citation

  • Christopher Jennison & Bruce W. Turnbull, 2006. "Adaptive and nonadaptive group sequential tests," Biometrika, Biometrika Trust, vol. 93(1), pages 1-21, March.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:1:p:1-21
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    File URL: http://hdl.handle.net/10.1093/biomet/93.1.1
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    Citations

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    Cited by:

    1. André Scherag & Johannes Hebebrand & Helmut Schäfer & Hans-Helge Müller, 2009. "Flexible Designs for Genomewide Association Studies," Biometrics, The International Biometric Society, vol. 65(3), pages 815-821, September.
    2. Jay Bartroff & Jinlin Song, 2016. "A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 3-19, March.
    3. Dejian Lai, 2010. "Group sequential tests under fractional Brownian motion in monitoring clinical trials," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(2), pages 277-286, June.
    4. Gregory P. Levin & Sarah C. Emerson & Scott S. Emerson, 2014. "An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size," Biometrics, The International Biometric Society, vol. 70(3), pages 556-567, September.
    5. Christopher Jennison & Bruce W. Turnbull, 2006. "Discussions," Biometrics, The International Biometric Society, vol. 62(3), pages 670-673, September.
    6. Sergey Tarima & Nancy Flournoy, 2022. "Most powerful test sequences with early stopping options," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(4), pages 491-513, May.
    7. Carl-Fredrik Burman & Christian Sonesson, 2006. "Rejoinder," Biometrics, The International Biometric Society, vol. 62(3), pages 680-683, September.
    8. Oke Gerke & Sören Möller, 2021. "Bland–Altman Limits of Agreement from a Bayesian and Frequentist Perspective," Stats, MDPI, vol. 4(4), pages 1-11, December.

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