没有对照组的分阶段干预
Brice Batomen1, Tarik Benmarhnia2,3
1Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
International journal of epidemiology
|October 15, 2024
概括
标准中断时间序列 (ITS) 模型可能会在没有对照组的情况下产生偏差的结果,用于分阶段干预. 本研究提出了适应ITS分析策略,以解决影响评估中的这一局限性.
科学领域:
- 流行病学 流行病学
- 计量经济学 计量经济学
- 生物统计学 生物统计学
背景情况:
- 双向固定效应模型在评估不同时间实施的分阶段干预方面存在局限性.
- 现有的替代策略往往假设有控制组的可用性,这并不总是可行的.
- 在没有控制组的情况下,中断时间序列 (ITS) 设计是潜在的替代方案.
研究的目的:
- 在分阶段干预的背景下调查标准中断时间序列 (ITS) 模型规范的局限性.
- 为了证明常见的ITS模型在应用于分阶段干预数据时可以产生偏差的结果.
- 为ITS分析提出新的,适应的分析策略,采用分阶段干预,从差异进步中汲取差异进步.
主要方法:
- 标准中断时间序列 (ITS) 模型规范的审查和批评.
- 模拟或经验分析,以说明标准ITS模型中的偏差与分阶段干预.
- 改进的ITS模型规范的开发灵感来自于最近的计量经济学文献关于分级差异差异.
主要成果:
- 标准ITS模型规范被证明可以产生对分阶段干预的偏见性影响评估.
- 偏差的程度取决于跨群体采用干预的时间和模式.
- 建议的替代模型规范在没有对照组的情况下提供更准确的估计.
结论:
- 标准的ITS模型不足以分析分阶段干预,特别是当没有控制组时.
- 适应ITS分析策略是必要的,以便在这种情况下进行可靠的影响评估.
- 这些发现对涉及分阶段干预的流行病学和计量经济学研究有重大影响.
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