Dept of Information Systems/Institute for Statistics, Hankamer School of Business, Baylor University, Waco, TX 76798-8005, USA.
Trends Ecol Evol. 1994 Jul;9(7):261-3. doi: 10.1016/0169-5347(94)90292-5.
When distributional assumptions for analysis of variance are suspect, and nonparametric methods are unavailable, ecologists frequently employ rank transformation (RT) methods. The technique replaces observations by their ranks, which are then analysed using standard parametric tests. RT methods are widely recommended in statistics texts and in manuals for packages like SAS and IMSL. They are robust and powerful for the analysis of additive factorial designs. Recently, however, RT methods have been found to be grossly inappropriate for use with non-additive models. This severe limitation remains largely unreported outside of the theoretical statistics literature. Our goal is to explain this shortcoming of RT methods.
当方差分析的分布假设受到怀疑，并且无法使用非参数方法时，生态学家通常会采用秩转换（RT）方法。该技术将观测值替换为它们的秩，然后使用标准参数检验对其进行分析。RT 方法在统计学教材和 SAS 和 IMSL 等软件包的手册中被广泛推荐。它们对于分析可加因子设计非常稳健且有效。然而，最近发现 RT 方法对于非加性模型的使用是非常不恰当的。这种严重的局限性在理论统计学文献之外基本上没有得到报道。我们的目标是解释 RT 方法的这一缺点。
