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Targeting the Optimal Design in Randomized Clinical Trials with Binary Outcomes and No Covariate: Simulation Study

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  • Chambaz Antoine
  • van der Laan Mark J.

Abstract

We undertake here a comprehensive simulation study of the theoretical properties that we derive in a companion article devoted to the asymptotic study of adaptive group sequential designs in the case of randomized clinical trials (RCTs) with binary treatment, binary outcome and no covariate. By adaptive design, we mean in this setting a RCT design that allows the investigator to dynamically modify its course through data-driven adjustment of the randomization probability based on data accrued so far without negatively impacting on the statistical integrity of the trial. By adaptive group sequential design, we refer to the fact that group sequential testing methods can be equally well applied on top of adaptive designs.The simulation study validates the theory. It notably shows in the estimation framework that the confidence intervals we obtain achieve the desired coverage even for moderate sample sizes. In addition, it shows in the testing framework that type I error control at the prescribed level is guaranteed and that all sampling procedures only suffer from a very slight increase of the type II error.A three-sentence take-home message is “Adaptive designs do learn the targeted optimal design and inference and testing can be carried out under adaptive sampling as they would under the targeted optimal randomization probability iid sampling. In particular, adaptive designs achieve the same efficiency as the fixed oracle design. This is confirmed by a simulation study, at least for moderate or large sample sizes, across a large collection of targeted randomization probabilities.”

Suggested Citation

  • Chambaz Antoine & van der Laan Mark J., 2011. "Targeting the Optimal Design in Randomized Clinical Trials with Binary Outcomes and No Covariate: Simulation Study," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-30, January.
    • Handle: RePEc:bpj:ijbist:v:7:y:2011:i:1:n:11
    DOI: 10.2202/1557-4679.1310
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    References listed on IDEAS

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    1. Chambaz Antoine & van der Laan Mark J., 2011. "Targeting the Optimal Design in Randomized Clinical Trials with Binary Outcomes and No Covariate: Theoretical Study," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-32, January.
    2. van der Laan Mark J. & Rubin Daniel, 2006. "Targeted Maximum Likelihood Learning," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-40, December.
    3. William F. Rosenberger & Nigel Stallard & Anastasia Ivanova & Cherice N. Harper & Michelle L. Ricks, 2001. "Optimal Adaptive Designs for Binary Response Trials," Biometrics, The International Biometric Society, vol. 57(3), pages 909-913, September.
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    Cited by:

    1. Antoine Chambaz & Mark J. Laan, 2014. "Inference in Targeted Group-Sequential Covariate-Adjusted Randomized Clinical Trials," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 104-140, March.
    2. Chambaz Antoine & van der Laan Mark J., 2011. "Targeting the Optimal Design in Randomized Clinical Trials with Binary Outcomes and No Covariate: Theoretical Study," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-32, January.

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