The Performance of Some Two-Sample Tests in Small Samples With and Without Censoring
有删失与无删失小样本中若干两样本检验的表现AI 解读 ↓
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有删失与无删失小样本中若干两样本检验的表现
- 研究问题
- 在指数与不同 Weibull 分布的小样本中，删失是否存在及删失时间是否相同，会如何影响三种两样本检验的水平和功效？
- 方法与思路
- 作者用 Monte Carlo 方法比较 F 比率、修正 F 比率及广义 Wilcoxon 检验，在两种样本规模和不同删失设定下获得功效曲线。
- 材料陈述的贡献
- 摘要称检验表现依赖分布与删失方式，指出 F 检验在 Weibull 情形下不稳健，且删失时间不同时修正 F 检验不适用。
- 阅读关注点
- 应核对 Weibull 参数、删失生成机制与检验水平，区分功效较高与水平正确，并查看不同设定下的完整比较曲线。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；具体分布参数、删失比例及功效曲线未提供，不能推广为普遍的检验优劣排序。
原文摘要
The power curves of three two-sample tests are compared in small samples from the exponential and four forms of the Weibull distribution with and without censoring. The tests considered are: F ratio, modified F ratio (F′ test), and a generalized Wilcoxon test (W test). Monte Carlo methods are used to obtain power curves for each test with sample sizes 20 and 50. The F test is known to be most efficient when sampling is from exponential distributions. If sampling is from exponential distributions and either there are no censored observations or all censored observations equal T, the F′ and W tests are nearly as powerful as F, with F′ being more powerful than W. If the times to censoring are not equal, the F′ test is not appropriate and the W test is nearly as powerful as F. When sampling is from Weibull distributions, with or without censoring, the F test is not robust; for example, its size is too small when the coefficient of variation is less than one. When sampling is from Weibull distributions and either there is no censoring or all censored observations have the same value, the F′ test is more powerful than the W test. If the times to censoring are not equal, the F′ test is not appropriate; the W test has the proper size and is a valid test.