对混因子的案例控制匹配被重新审视
Mohammad Ali Mansournia1, Charles Poole2
1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, PO Box, Tehran, 14155-6446, Iran. mansournia_ma@yahoo.com.
European journal of epidemiology
|September 14, 2023
概括
在案例控制研究中,匹配往往会产生偏见,与之前的假设相反. 这种偏见可能会扭曲结果,特别是当涉及多个混因素时,需要重新评估流行病学研究中的匹配策略.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 案例控制研究经常使用对混杂变量对控制进行匹配.
- 之前的理论模型假设单个混因子匹配在特定单调关联条件下有效消除偏差.
研究的目的:
- 在案例控制研究中重新评估混因子匹配的影响.
- 研究匹配,混和选择偏差之间的复杂相互作用.
主要方法:
- 通过对混因子进行匹配而引入的偏差的理论分析.
- 检查单个和多个混因素的场景.
- 评估关于单调关联的假设.
主要成果:
- 通过混器匹配几乎总是引入控制选择偏差,与混相互作用以创建净偏差.
- 关于偏差减少的先前假设是不够的,特别是当多个混因素需要控制时.
- 匹配使暴露分布更接近的启发式是有缺陷的.
结论:
- 在案例控制研究中,通过混因子进行匹配,比以前理解的更复杂的偏差.
- 现有的方法可能需要改进,以准确考虑匹配诱导偏差.
- 需要进一步的方法研究,以便在匹配策略中推进偏差评估.
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