在存在偏差放大时评估E值:一个模拟研究研究
Eric Barrette1, Lucas Higuera1, Kael Wherry2
1Medtronic, Plc, Minneapolis, MN, USA.
BMC medical research methodology
|March 28, 2024
概括
使用用于评估未测量的混的E值,在使用倾向得分方法时可能会误导. 这些方法可以加剧未被观察到的混乱失衡,膨胀E值并误解未测量的因素的真实影响.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 健康研究方法 卫生研究方法
背景情况:
- E值量化了未测量的混剂的最小协会强度,以解释观察到的治疗效应.
- 倾向得分方法 (PSM) 用于调整观察性研究中观察到的共变量.
- 均衡观察到的共变量也平衡未观察到的假设是无法测试的,可能不成立.
研究的目的:
- 为了检查不同程度的未观察到的混如何影响E值,当应用共变量调整时.
- 在不同未观察到的混场景下,使用回归和倾向得分方法来评估E值的性能.
主要方法:
- 使用蒙特卡洛模拟来评估治疗效果估计和E值灵敏度.
- 在观察到和未观察到的混因子之间越来越多的相关性中比较观察到/未观察到的混因子平衡,赔率比率和E值.
- 使用了通用线性模型 (GLM),反向概率加权和倾向得分匹配.
主要成果:
- 倾向得分方法 (匹配/加权) 可以加剧未被观察到的混因素失衡.
- 失衡程度取决于混因素,治疗和结果之间的相关性强度.
- 在PSM之后,E值往往会更大,因为未观察到的混因素会导致治疗效果估计的偏差更大.
结论:
- 在使用PSM时,E值可能不准确地表示改变治疗结果关联所需的未观察到的效应大小.
- 在使用倾向分数方法的研究中解释E值时,建议谨慎.
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