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贝叶斯样本大小计算在小n,顺序多重分配随机试验 (snSMART) 中
Fang Fang1, Roy N Tamura2, Thomas M Braun1
1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Pharmaceutical statistics
|January 23, 2025
概括
这项研究引入了两种新的方法来确定小n,顺序,多重分配,随机试验 (snSMART) 的样本大小,比较两个剂量与安慰剂. 这两种方法都有效地确保了临床试验效率所需的统计能力.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 药物开发 药物开发
背景情况:
- 小样本规模的临床试验需要高效的设计.
- 小n,顺序,多重分配,随机试验 (snSMART) 是适应这种设置的适应性设计.
- 之前的研究提出了贝叶斯的方法来估计snSMART的疗效.
研究的目的:
- 为snSMART设计提出和评估两种新的样本大小确定 (SSD) 方法.
- 在snSMART框架内,比较两个剂量水平与安慰剂.
- 确保在小型试验中确保治疗效果估计的足够的统计能力.
主要方法:
- 开发了基于平均覆盖标准 (ACC) 的两个样本大小确定 (SSD) 方法.
- 方法1:使用后方方差的单步计算.
- 方法2:为单阶段设计采用两步方法,使用调整因子 (AF).
- 通过模拟研究验证的方法.
主要成果:
- 两种建议的SSD方法都成功地实现了所需的统计功率.
- 通过新方法计算的样本大小适合于snSMART试验.
- 模拟证实了样本大小计算方法的可靠性.
结论:
- 建议的样本大小确定方法对于snSMART试验是有效的.
- 这些方法提高了用小样本大小进行临床试验的效率.
- 一个附带的小程序方便了这些SSD技术的实际应用.
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