Dept of Psychiatry, Center for Psychiatric Neurosciences, Lausanne University Hospital, Switzerland.
Lab Anim. 2024 Oct;58(5):448-452. doi: 10.1177/00236772241248509. Epub 2024 Aug 19.
Absence of statistical significance (i.e., > 0.05) in the results of a frequentist test comparing two samples is often used as evidence of absence of difference, or absence of effect of a treatment, on the measured variable. Such conclusions are often wrong because absence of significance may merely result from a sample size that is too small to reveal an effect. To conclude that there is no meaningful effect of a treatment/condition, it is necessary to use an appropriate statistical approach. For frequentist statistics, a simple tool for this goal is the 'two one-sided -test,' a form of equivalence test that relies on the a priori definition of a minimal difference considered to be relevant. In other words, the smallest effect size of interest should be established in advance. We present the principles of this test and give examples where it allows correct interpretation of the results of a classical -test assuming absence of difference. Equivalence tests are also very useful in probing whether certain significant results are also biologically meaningful, because when comparing large samples it is possible to find significant results in both an equivalence test and in a two-sample -test, assuming no difference as the null hypothesis.
在比较两个样本的频率检验结果中，如果没有统计学意义（即>0.05），通常被用作没有差异或治疗效果的证据，即在测量变量上。这种结论往往是错误的，因为缺乏显著性可能仅仅是由于样本量太小，无法揭示效应。为了得出治疗/条件没有有意义的效果的结论，有必要使用适当的统计方法。对于频率统计学，达到这一目标的一个简单工具是“两个单边检验”，这是一种等效检验形式，依赖于事先定义的认为相关的最小差异。换句话说，应该事先确定感兴趣的最小效应大小。我们介绍了这个测试的原则，并给出了一些例子，在这些例子中，它允许在假设没有差异的情况下正确解释经典测试的结果。等效检验在探究某些显著结果是否也具有生物学意义方面也非常有用，因为在比较大样本时，在等效检验和两样本检验中都有可能找到有意义的结果，假设零假设是没有差异。
