IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v174y2022ics0167947322001013.html
   My bibliography  Save this article

A hierarchical testing procedure for three arm non-inferiority trials

Author

Listed:
  • Ghosh, Santu
  • Guo, Wenge
  • Ghosh, Samiran

Abstract

Non-inferiority trials are becoming very popular for comparative effectiveness research. Non-inferiority trials establish that the effect of an experimental treatment is not worse than that of a reference treatment by more than a specified margin. A three-arm non-inferiority trial that includes the placebo, experimental treatment, and a reference treatment is considered. It has been criticized that the conventional approach for three-arm non-inferiority trials loses power for the non-inferiority hypothesis test unless the power of the assay sensitivity test is close to one. In order to overcome this situation, a novel hierarchical testing procedure with two stages for three-arm non-inferiority trials is developed. The family-wise error rate (FWER) is investigated analytically and numerically of the proposed test procedure. Numerical studies indicate that the suggested method controls FWER and has more power than the traditional approach particularly when the power of that assay sensitivity test is not close to one. Through these empirical studies, it is shown that the proposed method can be successfully applied in practice.

Suggested Citation

  • Ghosh, Santu & Guo, Wenge & Ghosh, Samiran, 2022. "A hierarchical testing procedure for three arm non-inferiority trials," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:csdana:v:174:y:2022:i:c:s0167947322001013
    DOI: 10.1016/j.csda.2022.107521
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947322001013
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2022.107521?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. Adelchi Azzalini, 2005. "The Skew‐normal Distribution and Related Multivariate Families," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(2), pages 159-188, June.
    2. Ghosh, Santu & Chatterjee, Arpita & Ghosh, Samiran, 2017. "Non-inferiority test based on transformations for non-normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 73-87.
    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. Wei Li & Yunqi Zhang & Niansheng Tang, 2023. "Non-Parametric Non-Inferiority Assessment in a Three-Arm Trial with Non-Ignorable Missing Data," Mathematics, MDPI, vol. 11(1), pages 1-26, January.

    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. Redivo, Edoardo & Nguyen, Hien D. & Gupta, Mayetri, 2020. "Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    2. Toshihiro Abe & Arthur Pewsey, 2011. "Sine-skewed circular distributions," Statistical Papers, Springer, vol. 52(3), pages 683-707, August.
    3. Egozcue, Martín & García, Luis Fuentes & Wong, Wing-Keung & Zitikis, Ricardas, 2011. "Do investors like to diversify? A study of Markowitz preferences," European Journal of Operational Research, Elsevier, vol. 215(1), pages 188-193, November.
    4. Castillo, Nabor O. & Gómez, Héctor W. & Leiva, Víctor & Sanhueza, Antonio, 2011. "On the Fernández-Steel distribution: Inference and application," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2951-2961, November.
    5. Cornelis J. Potgieter & Marc G. Genton, 2013. "Characteristic Function-based Semiparametric Inference for Skew-symmetric Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 471-490, September.
    6. Jamalizadeh, A. & Balakrishnan, N., 2010. "Distributions of order statistics and linear combinations of order statistics from an elliptical distribution as mixtures of unified skew-elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1412-1427, July.
    7. David Mayston, 2015. "Analysing the effectiveness of public service producers with endogenous resourcing," Journal of Productivity Analysis, Springer, vol. 44(1), pages 115-126, August.
    8. Lee, Sharon X. & McLachlan, Geoffrey J., 2022. "An overview of skew distributions in model-based clustering," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    9. Joe, Harry & Li, Haijun, 2019. "Tail densities of skew-elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 421-435.
    10. Penttinen, Antti & Moltchanova, Elena & Nummela, Ilkka, 2013. "Bayesian modeling of the evolution of male height in 18th century Finland from incomplete data," Economics & Human Biology, Elsevier, vol. 11(4), pages 405-415.
    11. Dvorkin Daniel & Biehs Brian & Kechris Katerina, 2013. "A graphical model method for integrating multiple sources of genome-scale data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(4), pages 469-487, August.
    12. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility," Microeconomics Working Papers 22058, East Asian Bureau of Economic Research.
    13. Shaobo Jin & Fan Yang-Wallentin, 2017. "Asymptotic Robustness Study of the Polychoric Correlation Estimation," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 67-85, March.
    14. Vernic, Raluca, 2006. "Multivariate skew-normal distributions with applications in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 38(2), pages 413-426, April.
    15. Batiz-Zuk, Enrique & Christodoulakis, George & Poon, Ser-Huang, 2015. "Credit contagion in the presence of non-normal shocks," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 129-139.
    16. Kampkötter, Patrick & Sliwka, Dirk, 2014. "Wage premia for newly hired employees," Labour Economics, Elsevier, vol. 31(C), pages 45-60.
    17. Martin Eling & Simone Farinelli & Damiano Rossello & Luisa Tibiletti, 2010. "Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 6(4), pages 290-304, September.
    18. Potgieter, C.J. & Lombard, F., 2012. "Nonparametric estimation of location and scale parameters," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4327-4337.
    19. Phil D. Young & Joshua D. Patrick & John A. Ramey & Dean M. Young, 2020. "An Alternative Matrix Skew-Normal Random Matrix and Some Properties," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 28-49, February.
    20. Douadia Bougherara & Laurent Piet, 2018. "On the role of probability weighting on WTP for crop insurance with and without yield skewness," Working Papers hal-02790605, HAL.

    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:eee:csdana:v:174:y:2022:i:c:s0167947322001013. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.