Abstract
Single-arm two-stage designs are commonly used in phase II of clinical trials. However, the use of randomization in phase II trials is currently increasing. We propose a randomized version of a Bayesian two-stage design due to Tan and Machin [4]. The idea is to select the two-stage sample sizes by ensuring a large posterior probability that the true response rate of the experimental treatment exceeds that of the standard agent, assuming that the experimental treatment is actually more effective. This optimistic assumption is realized by fixing virtual outcomes.
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Cellamare, M., Sambucini, V., Siena, F. (2014). Randomized Phase II Trials: A Bayesian Two-Stage Design. In: Lanzarone, E., Ieva, F. (eds) The Contribution of Young Researchers to Bayesian Statistics. Springer Proceedings in Mathematics & Statistics, vol 63. Springer, Cham. https://doi.org/10.1007/978-3-319-02084-6_27
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DOI: https://doi.org/10.1007/978-3-319-02084-6_27
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