A Monte Carlo study of the power of some two-sample tests
若干两样本检验功效的蒙特卡洛研究AI 解读 ↓
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若干两样本检验功效的蒙特卡洛研究
- 研究问题
- 在指数与威布尔分布的小样本中，删失和风险比是否恒定如何影响不同两样本检验的功效及其比较结果？
- 方法与思路
- 作者通过模拟比较 F 检验及其修正、Cox、对数秩和广义 Wilcoxon 检验，并从功效曲线估计渐近相对效率。
- 材料陈述的贡献
- 摘要称，指数分布下 F 检验功效最高；威布尔分布下需作修正，而风险比不恒定时两种广义 Wilcoxon 检验更有功效。
- 阅读关注点
- 阅读时应核对样本量、删失机制、威布尔参数、检验水平及模拟误差，并检查从功效曲线估计相对效率的依据。
- 阅读边界
- 仅据所给 OpenAlex 索引摘要，稿件版本未注明；具体模拟设置和数值未提供，功效比较不能外推至所有分布与删失机制。
原文摘要
The powers of several two-sample tests are compared by simulation for small samples from exponential and Weibull distributions with and without censoring. The tests considered include the F test, a modification for samples that are from Weibull distributions, Cox's test, Peto & Peto's log rank test, their generalized Wilcoxon test, a modified log rank test, and a generalized Wilcoxon test of Gehan. When samples are from exponential distributions, with or without censoring, the F test is the most powerful followed by two general groupings of tests: first the three non-Wilcoxon tests and then the two Wilcoxon tests. There is little difference in the power characteristics of the tests within each grouping. Estimates of the asymptotic relative efficiencies of the various tests relative to F are obtained from the normal probability plots of the power curves. When the samples are taken from Weibull distributions with constant hazard ratio, the F test is not robust and a modification is used. The results for this case are essentially the same as in the case of exponential distributions, with the modified F test as the most powerful. However, when the hazard ratio is nonconstant, the two generalizations of the Wilcoxon test have more power than the other tests.