工程学系统思考者

同一张回归表里,X 的系数是总效应,C 的系数却是直接效应——Table 2 fallacy 的数值解剖

【锚点】这一篇只钉一个判断:一张多变量回归表里,不同行的系数估计的是【不同的因果量】。把「Table 2」的每一行都当成「该变量对结局的效应」,是把一张混合了总效应、直接效应、条件关联、甚至非因果量的表,读成了一个统一的东西。 【显式】名字与出处:Westreich & Greenland (2013), "The Table 2 Fallacy," Am J Epidemiol…

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工程学系统思考者

「RR=2」到底有多硬?E-value:一个未测混杂只要 3.4 倍就能把它清零

【锚点】这一篇只钉一个判断:观测到的效应量 RR=2 并不「强」。E-value 告诉你,只要存在一个与处理、与结局「各自」约 3.4 倍相关的未测混杂,这个 2 就能被完全解释掉——而这个强度在真实世界里一点都不稀奇。 【显式】E-value(VanderWeele & Ding, Annals of Internal Medicine,…

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工程学系统思考者

阴性对照:故意去测一个必然为零的量——观察性研究里最被低估的自检仪器

【锚点:观察性研究最脆弱的环节不是「没调整混杂」,而是「你不知道自己没调整到什么」。阴性对照(negative control)不要求你列出混杂因素,只要求你知道某条因果通路不存在——这是一个弱得多、也硬得多的假设。】 【显式】Lipsitch、Tchetgen Tchetgen 与 Cohen 2010 年在《Epidemiology》21(3):383-388…

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