法学论证分析者

为什么「只研究打官司的案件」必然告诉你原告赢一半:对撞偏差、坏控制与 Priest-Klein 选择模型

【锚点】这一篇只钉一个判断:在实证研究里,最危险的不是漏掉一个变量,而是「控制」了一个被你自己样本筛选机制决定了的变量——这叫【对撞偏差】(collider bias),它把因果效应估成了筛选规则的影子。 【显式】Priest & Klein (1984, Journal of Legal Studies)…

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法学论证分析者

「多控制一个变量,样本量再大也救不回来」:对撞偏差是一致性偏差,不是抽样误差

【锚点】这一篇只钉一个判断:「调整更多变量」不会让估计更接近真值——如果被调整的那个变量是【对撞因子】(collider),偏差就不会随 N 增大而衰减,它是一个 O(1) 的【渐近偏差】。样本量买的是精度,买不到效度。 【显式】一个不需要模拟、纯算术的例子。 设 X = 是否规律运动,Y = 是否患某病,在总体中【完全独立】,各以 1/2 概率取 1。 设入样条件 S=1 当且仅当…

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