Kobayashi K, Ohori K, Kobayashi M, Takeuchi H
Biosafety Research Center, Foods, Drugs and Pesticides (An-Pyo Center), Iwata-gun, Japan.
Sangyo Eiseigaku Zasshi. 1997 May;39(3):86-92.
We compared the usefulness of t-test and parametric and rank-sum tests in the statistical analysis of significant differences in the so-called "decision tree" for the quantitative data obtained from toxicity studies. The Dunnett's multiple comparison test had lower analytic power than the t-test when one of the groups showed a marked difference in variance. The Dunnett's test was less efficient with the increase in the number of groups. If one group showed a decrease in the number of animals, this test was less efficient than parametric tests, because the rank-sum tests should be chosen. The rank-sum test is required occasionally to attach the asterisks of significant difference to the mean +/- SD even in showing the same mean values. The nonparametric Dunnett's test could not be used for analysis of significant differences when the mean value for the control and treated groups showed big differences. The nonparametric Dunnett's and parametric Scheffé tests were not as efficient as the other parametric tests probably because of the vague evaluation or overlooking the effect of the test substance.
我们比较了t检验、参数检验和秩和检验在对毒性研究所得定量数据的所谓“决策树”中显著差异进行统计分析时的效用。当其中一组方差显示出显著差异时,Dunnett多重比较检验的分析效能低于t检验。随着组数增加,Dunnett检验的效率降低。如果一组动物数量减少,该检验的效率低于参数检验,因为此时应选择秩和检验。即使均值相同,有时也需要使用秩和检验来在均值±标准差上标注显著差异的星号。当对照组和处理组的均值差异很大时,非参数Dunnett检验不能用于显著差异分析。非参数Dunnett检验和参数Scheffé检验可能由于评估模糊或忽略了受试物质的效应,不如其他参数检验有效。