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The asymptotic maximal procedure for subject randomization in clinical trials

机译:临床试验中受试者随机化的渐近最大法

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The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to the lack of the Markovian property of the conditional allocation probabilities. In this paper, we propose the asymptotic maximal procedure, which replaces the sequence-length-dependent conditional allocation probabilities with their asymptotic values. The new randomization procedure is compared with the original maximal procedure and few other randomization procedures with the maximum tolerated imbalance via simulations and is found to be a practical choice for future clinical trials.
机译:最大过程是限制的随机化方法,可以在最大容忍不平衡和分配序列长度的约束下最大化可行分配序列的数量。 它为所有可行序列分配相同的概率。 然而,由于缺乏条件分配概率的马尔科夫属性,其实施并不容易。 在本文中,我们提出了渐近的最大过程,其替换了它们的渐近值的序列长度依赖性条件分配概率。 将新的随机化程序与原始的最大程序进行比较,并通过模拟具有最大容忍不平衡的其他随机化程序,并被发现是未来临床试验的实用选择。

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