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Covariate‐adjusted response‐adaptive designs based on semiparametric approaches

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  • Hai Zhu
  • Hongjian Zhu

Abstract

We consider theoretical and practical issues for innovatively using a large number of covariates in clinical trials to achieve various design objectives without model misspecification. Specifically, we propose a new family of semiparametric covariate‐adjusted response‐adaptive randomization (CARA) designs and we use the target maximum likelihood estimation (TMLE) to analyze the correlated data from CARA designs. Our approach can flexibly achieve multiple objectives and correctly incorporate the effect of a large number of covariates on the responses without model misspecification. We also obtain the consistency and asymptotic normality of the target parameters, allocation probabilities, and allocation proportions. Numerical studies demonstrate that our approach has advantages over existing approaches, even when the data‐generating distribution is complicated.

Suggested Citation

  • Hai Zhu & Hongjian Zhu, 2023. "Covariate‐adjusted response‐adaptive designs based on semiparametric approaches," Biometrics, The International Biometric Society, vol. 79(4), pages 2895-2906, December.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:4:p:2895-2906
    DOI: 10.1111/biom.13849
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    References listed on IDEAS

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    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. 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. 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.
    4. Gruber Susan & van der Laan Mark J., 2010. "A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-18, August.
    5. Jianhua Hu & Hongjian Zhu & Feifang Hu, 2015. "A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 357-367, March.
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    Cited by:

    1. Li, Zhonghua & Luo, Lan & Wang, Jingshen & Feng, Long, 2025. "Efficient quantile covariate adjusted response adaptive experiments," Journal of Econometrics, Elsevier, vol. 249(PA).

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