This paper discusses disadvantages and limitations of the available inferential approaches in sequential clinical trials for treatment comparisons managed via response-adaptive randomization. Then, we propose an inferential methodology for response-adaptive designs which, by exploiting a variance stabilizing transformation into a bootstrap framework, is able to overcome the above-mentioned drawbacks, regardless of the chosen allocation procedure as well as the desired target. We derive the theoretical properties of the suggested proposal, showing its superiority with respect to likelihood, randomization and design-based inferential approaches. Several illustrative examples and simulation studies are provided in order to confirm the relevance of our results.

本文讨论了在顺序临床试验中通过反应适应性随机管理进行治疗比较的可用推论方法的缺点和局限性。然后，我们提出了一种用于响应自适应设计的推论方法，该方法通过利用将方差稳定化变换转换为自举框架，能够克服上述缺点，而与选择的分配过程以及所需的目标无关。我们得出建议的建议的理论特性，显示其在可能性，随机性和基于设计的推理方法方面的优越性。为了证实我们的结果的相关性，提供了一些说明性的例子和模拟研究。