Hooton J W
Department of Biochemistry, University of Alberta, Edmonton, Canada.
Comput Methods Programs Biomed. 1991 May;35(1):43-51. doi: 10.1016/0169-2607(91)90103-z.
Randomization (permutation) tests free the experimenter from the constraints of random sampling, a known error distribution and equal variances, to give a direct answer to the question "how likely is such a large (or small) result if the applied treatments had no effect?" The "result" may be the difference in mean responses, a correlation coefficient or any other value of interest. A randomization test is not a different statistical test but a different, and always valid, method of determining statistical significance. The familiar t-test and F-test can be carried out by data permutation without any parametric assumptions being fulfilled. A particular advantage of this method is that unbalanced designs and missing values are easily accommodated. Even with only a small number of subjects the number of permutations will be large and a computer is necessary if the randomization test is to be of practical value. To make this method of determining statistical significance generally available an interactive microcomputer program, forming a comprehensive package for the design and analysis of experiments, has been prepared.
随机化（排列）检验使实验者摆脱了随机抽样、已知误差分布和方差齐性的限制，直接回答“如果所应用的处理没有效果，出现如此大（或小）的结果的可能性有多大？”这个问题。“结果”可能是平均反应的差异、相关系数或任何其他感兴趣的值。随机化检验不是一种不同的统计检验，而是一种不同的、且始终有效的确定统计显著性的方法。熟悉的t检验和F检验可以通过数据排列来进行，而无需满足任何参数假设。这种方法的一个特别优点是，不平衡设计和缺失值很容易处理。即使只有少量受试者，排列的数量也会很大，如果随机化检验要有实际价值，就需要一台计算机。为了使这种确定统计显著性的方法普遍可用，已经编写了一个交互式微机程序，它构成了一个用于实验设计和分析的综合软件包。
