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Optimal response and covariate-adaptive biased-coin designs for clinical trials with continuous multivariate or longitudinal responses

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  • Atkinson, Anthony C.
  • Biswas, Atanu

Abstract

Adaptive randomization of the sequential construction of optimum experimental designs is used to derive biased-coin designs for longitudinal clinical trials with continuous responses. The designs, coming from a very general rule, target pre-specified allocation proportions for the ranked treatment effects. Many of the properties of the designs are similar to those of well understood designs for univariate responses. A numerical study illustrates this similarity in a comparison of four designs for longitudinal trials. Designs for multivariate responses can likewise be found, requiring only the appropriate information matrix. Some new results in the theory of optimum experimental design for multivariate responses are presented.

Suggested Citation

  • Atkinson, Anthony C. & Biswas, Atanu, 2017. "Optimal response and covariate-adaptive biased-coin designs for clinical trials with continuous multivariate or longitudinal responses," LSE Research Online Documents on Economics 66761, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:66761
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    References listed on IDEAS

    as
    1. Brajendra C. Sutradhar & Atanu Biswas & Wasimul Bari, 2005. "Marginal Regression for Binary Longitudinal Data in Adaptive Clinical Trials," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(1), pages 93-113, March.
    2. Hu, Feifang & Rosenberger, William F., 2003. "Optimality, Variability, Power: Evaluating Response-Adaptive Randomization Procedures for Treatment Comparisons," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 671-678, January.
    3. Lanju Zhang & William F. Rosenberger, 2006. "Response-Adaptive Randomization for Clinical Trials with Continuous Outcomes," Biometrics, The International Biometric Society, vol. 62(2), pages 562-569, June.
    4. Anthony C. Atkinson & Atanu Biswas, 2005. "Bayesian Adaptive Biased-Coin Designs for Clinical Trials with Normal Responses," Biometrics, The International Biometric Society, vol. 61(1), pages 118-125, March.
    5. Anthony C. Atkinson, 2002. "The comparison of designs for sequential clinical trials with covariate information," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(2), pages 349-373, June.
    6. 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.
    7. Lanju Zhang & William F. Rosenberger, 2007. "Response‐adaptive randomization for survival trials: the parametric approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(2), pages 153-165, March.
    8. Jun Shao & Xinxin Yu & Bob Zhong, 2010. "A theory for testing hypotheses under covariate-adaptive randomization," Biometrika, Biometrika Trust, vol. 97(2), pages 347-360.
    9. A. C. Atkinson, 2015. "Optimum designs for two treatments with unequal variances in the presence of covariates," Biometrika, Biometrika Trust, vol. 102(2), pages 494-499.
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    More about this item

    Keywords

    biased-coin design; covariate balance; effective number of observations; ethical allocation; equivalence theorem; multivariate DA-optimality; multivariate loss; power skewed allocation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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