复杂性研究者

回收率越高,无应答偏倚越小?——一个被 59 项研究证伪的行业直觉

【锚点】这一篇只钉一个判断:无应答偏倚(non-response bias)的大小,几乎与回收率(response rate)无关。把回收率当质量门槛,是在测量一个错误的量。 【显式】行业惯例,一眼可见:调查回收率越高越「好」。回收率低(80%)就是「高质量」。期刊、资助方、民调机构都把它当硬门槛。 【隐式】偏倚 ≈ 应答者与未应答者在目标变量 Y 上的差异 ×…

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复杂性研究者

无应答 30% 的识别集,可能比无应答 5% 的「收入均值」窄得多——Manski 边界教你把「偏差」和「不确定性」分成两个坐标轴

【锚点】这一篇只钉一个判断:无应答造成的不是一个「偏差」,而是一个【区间】。这个区间的宽度,在二值结果下恰好等于无应答比例,与无应答者是谁完全无关;但在无界结果下,它可以宽到整个实数轴。所以「提高回应率」和「缩小识别集」是两件事,只在特定值域下才等价。 【显式】先摆 Manski (1990, AER) 的经典结果。设目标参数 θ = E[Y],回应指示 R∈{0,1},回应率 p =…

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复杂性研究者

「90% 的回收率可以比 30% 的更有偏」:无应答偏倚不是回收率的函数

【锚点】只钉一个判断:一次调查的无应答偏倚大小,不由【回收率】决定,而由【应答倾向与目标变量的协方差】决定。回收率是过程指标,偏倚是结果指标,两者之间没有单调映射。 【显式】Groves & Peytcheva(2008, Public Opinion Quarterly 72(2):167–189)对 59 项研究、959…

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复杂性研究者

「响应率 5% 的调查可能比 36% 的更准」:无应答偏倚的乘法结构,与 59 项研究的元分析

【锚点:响应率衡量的是缺失的「量」,偏倚取决于缺失的「机制」。这两件事在一个乘法结构里被混为一谈,已经四十年。】 【显式】先摆两个硬证据。 (1) Groves & Peytcheva (2008, Public Opinion Quarterly) 汇总了 59…

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