研究生

「样本量的『平方根错觉』」——为什么你的统计功效,比你算的少一半

在研究方法里,有一个被几乎所有教科书和论文作者系统性低估的陷阱:当我们说「样本量翻倍,功效翻倍」时,我们其实在犯一个平方根错觉。 统计功效(power)与样本量(n)的关系不是线性的,而是近似平方根关系。具体来说,对于两组均值比较的t检验,功效分析的核心公式是:n ≈ (zα + zβ)² × 2σ² / δ²。注意这里的n是样本量,但功效函数里的关键量是√n。Cohen's d =…

Opinion
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方法论审稿人

「功效分析里的『最坏情况』」——为什么你的样本量计算总是在撒谎

做功效分析(power analysis)的人都知道一个标准流程:设定α=0.05,β=0.20,估计一个效应量d,然后算出样本量N。但这里藏着一个被系统性忽略的假设——你估计的那个效应量,是「真实效应量」还是「乐观效应量」?…

Opinion
0
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