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响应适应性随机化的稳定性

Xiaoqing Ye¹, Feifang Hu², Wei Ma¹

¹Institute of Statistics and Big Data, Renmin University of China, Beijing 100872, China.

|May 31, 2024

概括

双适应性偏向硬币设计 (DBCD) 即使在模型错误规范的情况下也保持稳健. 在这些条件下,ANCOVA II模型提供了最有效的治疗效果估计.

科学领域:

生物统计学生物统计学
临床试验设计临床试验设计
统计建模统计建模

背景情况:

响应适应性随机化,就像双重适应性偏见硬币设计 (DBCD),根据响应调整主体分配.
现有的DBCD研究假定正确的模型规范,但其在错误规范下的性能不太了解.

研究的目的:

为了评估双重适应性偏见硬币设计 (DBCD) 对设计和分析模型错误规范的稳定性.
评估错误指定的回归模型对DBCD.内治疗效果估计和推断的影响.

主要方法:

在设计模型错误规范下评估分配比例的理论性质.
研究了三种线性回归模型 (平均差异,ANCOVA I,ANCOVA II) 用任意错误指定的分析模型来估计治疗效果.
治疗效果估计器的衍生一致性和异常正常性.

主要成果:

在 DBCD 中的分配比例保持一致性和非对称的正常性,即使在设计模型的错误规格.
在错误指定的回归模型中,治疗效果估计器的一致性和异常正常性被保留.
该ANCOVAII模型,结合共变量对治疗相互作用,提供了统计学上最有效的估计器.

结论:

双适应性偏见硬币设计 (DBCD) 在设计和分析方面都表现出对模型错误规范的稳定性.
这些发现支持在现实场景中使用DBCD,在现实场景中,模型假设可能不完全成立.
在错误指定的DBCD框架内推ANCOVA II,因为它在治疗效果估计中的效率更高.

关键词:

安科瓦一号 (ANCOVA I) 是一个城市.安科瓦二世 (ANCOVA II) 是一个平均值差异 - 平均值差异具有双重适应性的偏见硬币设计.模型错误的规格错误

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