Zhou X H, Gao S, Hui S L
Department of Medicine, Indiana University School of Medicine, Indianapolis 46202-5200, USA.
Biometrics. 1997 Sep;53(3):1129-35.
Standard methods of using the t-test and the Wilcoxon test have deficiencies for comparing the means of two skewed log-normal samples. In this paper, we propose two new methods to overcome these deficiencies: (1) a likelihood-based approach and (2) a bootstrap-based approach. Our simulation study shows that the likelihood-based approach is the best in terms of the type I error rate and power when data follow a log-normal distribution.
使用t检验和威尔科克森检验的标准方法在比较两个偏态对数正态样本的均值时存在缺陷。在本文中,我们提出了两种新方法来克服这些缺陷:(1)基于似然的方法和(2)基于自助法的方法。我们的模拟研究表明,当数据服从对数正态分布时,基于似然的方法在I型错误率和检验功效方面是最佳的。