IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v110y2015i509p357-367.html
   My bibliography  Save this article

A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics

Author

Listed:
  • Jianhua Hu
  • Hongjian Zhu
  • Feifang Hu

Abstract

Response-adaptive designs have recently attracted more and more attention in the literature because of its advantages in efficiency and medical ethics. To develop personalized medicine, covariate information plays an important role in both design and analysis of clinical trials. A challenge is how to incorporate covariate information in response-adaptive designs while considering issues of both efficiency and medical ethics. To address this problem, we propose a new and unified family of covariate-adjusted response-adaptive (CARA) designs based on two general measurements of efficiency and ethics. Important properties (including asymptotic properties) of the proposed procedures are studied under categorical covariates. This new family of designs not only introduces new desirable CARA designs, but also unifies several important designs in the literature. We demonstrate the proposed procedures through examples, simulations, and a discussion of related earlier work.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:jnlasa:v:110:y:2015:i:509:p:357-367
    DOI: 10.1080/01621459.2014.903846
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2014.903846
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01621459.2014.903846?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Alessandro Baldi Antognini & Alessandra Giovagnoli, 2010. "Compound optimal allocation for individual and collective ethics in binary clinical trials," Biometrika, Biometrika Trust, vol. 97(4), pages 935-946.
    3. Tymofyeyev, Yevgen & Rosenberger, William F. & Hu, Feifang, 2007. "Implementing Optimal Allocation in Sequential Binary Response Experiments," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 224-234, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hengtao Zhang & Guosheng Yin, 2021. "Response‐adaptive rerandomization," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1281-1298, November.
    2. Waverly Wei & Xinwei Ma & Jingshen Wang, 2023. "Fair Adaptive Experiments," Papers 2310.16290, arXiv.org.
    3. 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.
    4. Yi, Yanqing & Wang, Xikui, 2023. "A Markov decision process for response adaptive designs," Econometrics and Statistics, Elsevier, vol. 25(C), pages 125-133.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alessandro Baldi Antognini & Marco Novelli & Maroussa Zagoraiou, 2022. "A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials," Statistical Papers, Springer, vol. 63(1), pages 157-180, February.
    2. Yanqing Yi & Yuan Yuan, 2013. "An optimal allocation for response-adaptive designs," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1996-2008, September.
    3. Yi, Yanqing & Wang, Xikui, 2023. "A Markov decision process for response adaptive designs," Econometrics and Statistics, Elsevier, vol. 25(C), pages 125-133.
    4. 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.
    5. Sofía S. Villar & William F. Rosenberger, 2018. "Covariate†adjusted response†adaptive randomization for multi†arm clinical trials using a modified forward looking Gittins index rule," Biometrics, The International Biometric Society, vol. 74(1), pages 49-57, March.
    6. Uttam Bandyopadhyay & Rahul Bhattacharya, 2009. "Response adaptive procedures with dual optimality," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 353-367, August.
    7. Alessandro Baldi Antognini & Marco Novelli & Maroussa Zagoraiou, 2022. "A new inferential approach for response-adaptive clinical trials: the variance-stabilized bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 235-254, March.
    8. Uttam Bandyopadhyay & Atanu Biswas & Shirsendu Mukherjee, 2009. "Adaptive two-treatment two-period crossover design for binary treatment responses incorporating carry-over effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 13-33, March.
    9. Hengtao Zhang & Guosheng Yin, 2021. "Response‐adaptive rerandomization," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1281-1298, November.
    10. Hanan Hammouri & Marwan Alquran & Ruwa Abdel Muhsen & Jaser Altahat, 2022. "Optimal Weighted Multiple-Testing Procedure for Clinical Trials," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
    11. Biswas, Atanu & Bhattacharya, Rahul, 2010. "An optimal response-adaptive design with dual constraints," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 177-185, February.
    12. 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.
    13. Jennifer Proper & Thomas A. Murray, 2023. "An alternative metric for evaluating the potential patient benefit of response‐adaptive randomization procedures," Biometrics, The International Biometric Society, vol. 79(2), pages 1433-1445, June.
    14. Li-Xin, Zhang, 2006. "Asymptotic results on a class of adaptive multi-treatment designs," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 586-605, March.
    15. Mandal, Saumen & Biswas, Atanu & Trandafir, Paula Camelia & Islam Chowdhury, Mohammad Ziaul, 2013. "Optimal target allocation proportion for correlated binary responses in a 2×2 setup," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 1991-1997.
    16. Alessandra Giovagnoli, 2021. "The Bayesian Design of Adaptive Clinical Trials," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    17. 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.
    18. Yuan, Ao & Chai, Gen Xiang, 2008. "Optimal adaptive generalized Polya urn design for multi-arm clinical trials," Journal of Multivariate Analysis, Elsevier, vol. 99(1), pages 1-24, January.
    19. Biswas, Atanu & Bhattacharya, Rahul, 2011. "Optimal response-adaptive allocation designs in phase III clinical trials: Incorporating ethics in optimality," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1155-1160, August.
    20. Uttam Bandyopadhyay & Atanu Biswas, 2018. "Fixed-width confidence interval for covariate-adjusted response-adaptive designs," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(2), pages 353-371, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jnlasa:v:110:y:2015:i:509:p:357-367. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.