Late Development Statistics, Merck Sharp & Dohme Corp., 126 E. Lincoln Avenue, P.O. Box 2000, Rahway, NJ, 07065-0900, USA.
Stat Med. 2012 Apr 13;31(8):701-23. doi: 10.1002/sim.4447. Epub 2011 Dec 12.
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.
临床试验中不均衡分配的需求日益增长。最常见的方法是通过区组随机化实现不均衡分配。然而,为了更好地逼近小样本中的分配比例、减少开放标签研究中的选择偏差,或者平衡基线协变量,可能需要其他分配程序。当这些分配程序推广到不均衡分配时,需要特别注意在每个分配步骤中保持分配比例。本文提供了一种将有偏硬币随机化扩展到保持每个分配的分配比例的方法。建议的扩展适用于仅在治疗组总和上平衡的有偏硬币随机化,以及在每个分配时使用随机有偏硬币元素的协变量自适应程序。通过模拟描述了分配比例保持有偏硬币随机化的平衡和最小化的属性。结果表明,这些程序在渐近意义上可以防止重随机化分布的转移,这种转移是针对某些 1:2 分配的最小化例子确定的。本文还明确推导出了任意不均衡分配程序中治疗效果差异的重随机化分布的渐近转移。