在仪器化差异差异方法下进行组序列测试
Samrat Roy1, Ting Ye2, Ashkan Ertefaie3
1Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Statistics in medicine
|June 22, 2023
概括
本研究引入了一种使用仪器差异差异 (iDiD) 进行因果推理的新组序列测试方法. 该方法提供有效的推断,即使没有测量混,更早地检测药物副作用.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 观察性研究 观察性研究
背景情况:
- 没有测量的混对观察性研究中的因果推断构成了重大挑战.
- 仪器化差异差异 (iDiD) 提供了一种方法,通过使用仪器变量和差异差异来解决混.
- 现有方法在未测量的混因素存在时可能无法提供有效的推断.
研究的目的:
- 提出一种使用仪器差异框架 (iDiD) 进行因果推理的新型组序列测试方法.
- 确保有效的统计推断,即使存在未测量的混因素.
- 为了在正在进行的观察性研究中更早地检测治疗效应.
主要方法:
- 开发了一种集体顺序测试方法,与iDiD方法集成.
- 在使用累积数据的顺序时间点估计的平均或条件平均治疗效果.
- 根据零假设,使用M-估计,并利用对顺序边界的alpha-spending函数推导出测试统计的联合分布.
主要成果:
- 拟议的iDiD组顺序方法在未测量的混因素存在时提供了有效的推断.
- 在合成数据和现实世界医疗保健数据库 (Clinformatics Data Mart 数据库) 上进行评估.
- 在其退出市场之前,成功检测出罗菲可西布和急性心肌梗塞之间的显著不良关联.
结论:
- 新的组序列测试方法通过解决未测量的混,增强了从观测数据的因果推断.
- 这种方法可以及时识别潜在的安全问题或治疗效应.
- 该方法在药物监测和临床研究中证明了其实用性.
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