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双臂等额分配试验受限随机化设计中个体分配的分配可预测性

Allocation Predictability of Individual Assignments in Restricted Randomization Designs for Two-Arm Equal Allocation Trials.

作者信息

Zhao Wenle, Livingston Sherry

机构信息

Medical University of South Carolina, Charleston, South Carolina, USA.

出版信息

Stat Med. 2025 Feb 10;44(3-4):e10343. doi: 10.1002/sim.10343.

Abstract

This manuscript derives the allocation predictability measured by the correct guess probability and the probability of being deterministic for individual treatment assignments, as well as the averages of a randomization sequence, based on the treatment imbalance transition matrix and the conditional allocation probability. The methods described are applicable to restricted randomization designs that satisfy the following criteria: (1) two-arm equal allocation, (2) restriction of maximum tolerated imbalance, and (3) conditional allocation probability fully determined by the observed current treatment imbalance. Analytical results indicate that, for two-arm equal allocation trials, allocation predictability alternates by the odd/even sequence order of the treatment assignment. Additionally, the sequence average allocation predictability converges to its asymptotic value significantly more slowly than the allocation predictability for individual assignment does. Consequently, comparisons of allocation predictability between different randomization designs based on sequence averages are sensitive to sequence length. Using sequence average allocation predictability may underestimate the risk of selection bias for individual assignment. This discrepancy is particularly pronounced for short sequence lengths, where individual assignment predictability can be substantially higher than the sequence average.

摘要

本手稿基于治疗不平衡转移矩阵和条件分配概率,推导了通过正确猜测概率和个体治疗分配的确定性概率衡量的分配可预测性,以及随机化序列的平均值。所描述的方法适用于满足以下标准的受限随机化设计:(1)双臂均等分配;(2)最大耐受不平衡的限制;(3)条件分配概率完全由观察到的当前治疗不平衡决定。分析结果表明,对于双臂均等分配试验,分配可预测性按治疗分配的奇/偶序列顺序交替。此外,序列平均分配可预测性收敛到其渐近值的速度明显比个体分配的分配可预测性慢得多。因此,基于序列平均值的不同随机化设计之间的分配可预测性比较对序列长度敏感。使用序列平均分配可预测性可能会低估个体分配的选择偏倚风险。这种差异在短序列长度时尤为明显,此时个体分配可预测性可能会大大高于序列平均值。

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