为什么 R pwr.2p.test 给出的样本量与 G*Power 不同？

Question

我想知道所需的样本量。在

library(pwr)
pwr.2p.test(h = ES.h(0.022,0.001),sig.level = 0.05,power = 0.8,alternative = "greater")

给出结果

     Difference of proportion power calculation for binomial distribution (arcsine transformation) 

              h = 0.2344905
              n = 224.8784
      sig.level = 0.05
          power = 0.8
    alternative = greater

NOTE: same sample sizes

在 G*Power 工具中，结果是

我的问题是，为什么 R 和 G*Power 的样本量差异如此之大（225 对 318）？谢谢

Answer 1

差异的原因在于pwr:pwr.2p.test使用不同的方法来计算 Cohen 的效应量 h，即它使用 arcsin 变换。相比之下，GPower 以及统计库中的内置功率测试使用的是近似值。

要匹配 pwr 和 GPower 之间的结果，请转到 GPower 并在输入模型详细信息时，select底部的“选项”并打开反正弦转换。

引自 GPower 文档（粗体由我添加）：

Numerous procedures have been proposed to test the null hypothesis that two independent proportions are identical (Cohen, 1988; DAgostino, Chase, & Belanger, 1988; Suissa & Shuster, 1985; Upton, 1982), and G*Power 3 implements several of them. The simplest procedure is a z test with optional arcsin transformation and optional continuity correction. Besides these two computational options, one can also choose whether Cohens effect size measure h or, alternatively, two proportions are used to specify the alternate hypothesis. With the options Use continuity correction off and Use arcsin transform on, the procedure calculates power values close to those tabulated by Cohen (1988, chap. 6). With both Use continuity correction and Use arcsin transform off, the uncorrected 2 approximation is computed (Fleiss, 1981); with Use continuity correction on and Use arcsin transform off, the corrected 2 approximation is computed (Fleiss, 1981).

来源：https://paperity.org/p/19044909/g-power-3-a-flexible-statistical-power-analysis-program-for-the-social-behavioral-and

为什么 R pwr.2p.test 给出的样本量与 G*Power 不同？

Why R pwr.2p.test gives different sample size than G*Power?

r

sample-size

power-analysis