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Model robust designs for survival trials

Author

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  • Konstantinou, Maria
  • Biedermann, Stefanie
  • Kimber, Alan

Abstract

The exponential-based proportional hazards model is often assumed in time-to-event experiments but may only approximately hold. Deviations in different neighbourhoods of this model are considered that include other widely used parametric proportional hazards models and the data are assumed to be subject to censoring. Minimax designs are then found explicitly, based on criteria corresponding to classical c- and D-optimality. Analytical characterisations of optimal designs are provided which, unlike optimal designs for related problems in the literature, have finite support and thus avoid the issues of implementing a density-based design in practice. Finally, the proposed designs are compared with the balanced design that is traditionally used in practice, and recommendations for practitioners are given.

Suggested Citation

  • Konstantinou, Maria & Biedermann, Stefanie & Kimber, Alan, 2017. "Model robust designs for survival trials," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 239-250.
    • Handle: RePEc:eee:csdana:v:113:y:2017:i:c:p:239-250
    DOI: 10.1016/j.csda.2016.10.013
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    References listed on IDEAS

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    1. Xiaojian Xu, 2009. "Robust designs for misspecified exponential regression models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(2), pages 179-193, March.
    2. J. McGree & J. Eccleston, 2010. "Investigating design for survival models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 72(3), pages 295-311, November.
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