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Preserving the allocation ratio at every allocation with biased coin randomization and minimization in studies with unequal allocation

机译:在分配不均等的研究中,通过偏向硬币随机化和最小化来保持每次分配的分配率

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摘要

The demand for unequal allocation in clinical trials is growing. Most commonly, the unequal allocation is achieved through permuted block randomization. However, other allocation procedures might be required to better approximate the allocation ratio in small samples, reduce the selection bias in open-label studies, or balance on baseline covariates. When these allocation procedures are generalized to unequal allocation, special care is to be taken to preserve the allocation ratio at every allocation step. This paper offers a way to expand the biased coin randomization to unequal allocation that preserves the allocation ratio at every allocation. The suggested expansion works with biased coin randomization that balances only on treatment group totals and with covariate-adaptive procedures that use a random biased coin element at every allocation. Balancing properties of the allocation ratio preserving biased coin randomization and minimization are described through simulations. It is demonstrated that these procedures are asymptotically protected against the shift in the rerandomization distribution identified for some examples of minimization with 1:2 allocation. The asymptotic shift in the rerandomization distribution of the difference in treatment means for an arbitrary unequal allocation procedure is explicitly derived in the paper.
机译:对临床试验中分配不均的需求正在增长。最常见的是,不等分配是通过置换块随机化来实现的。但是,可能需要其他分配程序才能更好地估计小样本中的分配比率,减少开放标签研究中的选择偏倚或平衡基线协变量。当将这些分配程序推广到不平等分配时,应特别注意在每个分配步骤中保持分配比率。本文提供了一种方法,可以将有偏的硬币随机化扩展到不平等分配,从而在每次分配时都保留分配比率。建议的扩展使用仅在治疗组总数上保持平衡的偏向硬币随机化工作,以及在每次分配时均使用随机偏向硬币元素的协变量自适应程序。通过仿真描述了分配比例保持偏向硬币随机化和最小化的平衡特性。证明了这些过程在渐近保护下不受针对1:2分配的最小化示例所确定的重新随机化分布的偏移。本文明确推导了任意不相等分配过程的处理方式差异的重新随机分布中的渐近转移。

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