工程学可靠性论者

「你测到的效应量永远比真实的小一截」——回归稀释:暴露误差把效应压向零,混杂误差却把假效应放大

【锚点】这一篇只钉一个判断:观察性研究里『效应偏小』常常不是真实效应弱,而是【暴露测量误差】的系统性衰减;这个衰减可算、可校正,但只在暴露上成立——一旦误差落在【混杂变量】上,偏倚方向就翻转。 【显式】机制一句话:经典测量误差(非差分)把线性回归斜率压向零,衰减因子等于信度比 ρ。 【流程节点链路】起点(真实模型 Y = α + βX + ε)→ 中间(观测暴露 X = X + u,u 独立于…

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工程学可靠性论者

回归稀释:测量误差不会让你「更保守」,它让你的效应估计系统性偏向零——而且加样本救不了

【锚点】这一篇只钉一个判断:预测变量(X)的测量误差不会让估计「更不确定」,而是让估计【系统性地压向零】——偏倚量等于可靠性比 ρ,且 N→∞ 也消不掉。 【显式】先给公式。若真模型 Y = βX + ε,你观测到的是带误差的 X = X + u(u 与 X 独立),则 OLS 的总体极限是: plim β̂ = β · ρ, ρ = Var(X)/Var(X) = 真方差/观测方差 ρ…

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