标题： 1:1是否总是最有力的？ 为什么不平等分配值得更广泛的考虑 显示英文标题

标题： Is 1:1 Always Most Powerful? Why Unequal Allocation Merits Broader Consideration

摘要： 在随机对照试验中，将相等数量的患者分配到每个试验组的原则被广泛接受为最大化试验统计功效的标准策略。 然而，这种长期存在的信念只有在治疗组的结果方差相等的情况下才成立，而这一条件在实践中往往并不满足。 本文质疑了仅依赖于均等随机化（ER）的普遍做法，并认为偏离1:1的比例可能是合理且有益的。 我们通过两个模拟案例研究来证明这一原则，一个以二元终点为例，另一个以连续终点为例，比较均等随机化（ER）与预先计划的固定不均等随机化和针对Neyman分配的响应自适应随机化的性能。 我们的结果表明，不均等比例可以在同时将更大比例的患者分配到优势治疗组方面优于均等随机化。 我们得出结论，当怀疑存在不均等方差时，应战略性地决定分配比例，而不是默认采用1:1的比例，这构成了更优的设计选择。 显示英文摘要

摘要： The principle of allocating an equal number of patients to each arm in a randomized controlled trial is widely accepted as the standard strategy for maximising the trial's statistical power. However, this long-held belief only holds true if the treatment groups have equal outcome variances, a condition that is often not met in practice. This paper questions the prevalent practice of exclusively defaulting to equal randomisation (ER) and posits that a departure from a 1:1 ratio can be both valid and advantageous. We demonstrate this principle through two simulated case studies, one with a binary endpoint and one with a continuous endpoint, comparing the performance of ER against preplanned Fixed Unequal Randomisation and Response-Adaptive Randomisation targeting Neyman allocation. Our results show that unequal ratios can increase statistical power while simultaneously allocating a substantially larger proportion of patients to the superior treatment arm compared to ER. We conclude that, when unequal variances are suspected, a strategic decision regarding the allocation ratio, rather than a default 1:1, constitutes the superior design choice.