Koehnle Thomas J, Schank Jeffrey C
Department of Biology, Hiram College.
J Comp Psychol. 2009 Nov;123(4):452-8. doi: 10.1037/a0017435.
The doctrine of pseudoreplication (DP) offers specific advice on how to ensure statistical independence and compute F-ratios properly when testing a null hypothesis. Our target article showed that this advice can lead to problems in experimental design and analysis. Though a few commenters attempt to defend DP, none offered substantive evidence that our modeling results were incorrect. In our response, we further highlight the complications surrounding definitions of experimental units. In particular, we show that the definition of independence assumed in DP is inconsistent with independence as defined in probability theory. We show that interconnectedness across levels of analysis is pervasive, and that no simple set of rules or procedures can help experimenters avoid this problem. We argue that the relevance or interference of a particular level of analysis can be determined only after an experiment is done. In our view, analytical methods must be designed to match experiments, the opposite of the advice offered in DP. Finally, we emphasize the weakness of null testing and the inability of p values to predict whether a result will generalize or be replicated.
伪重复原则（DP）针对在检验零假设时如何确保统计独立性以及正确计算F比率提供了具体建议。我们的目标文章表明，这条建议可能会在实验设计和分析中引发问题。尽管有几位评论者试图为DP辩护，但没有人提供实质性证据证明我们的建模结果是错误的。在我们的回应中，我们进一步强调了围绕实验单位定义的复杂性。特别是，我们表明DP中假设的独立性定义与概率论中定义的独立性不一致。我们表明，分析层次之间的相互联系是普遍存在的，而且没有一套简单的规则或程序能够帮助实验者避免这个问题。我们认为，只有在实验完成后才能确定特定分析层次的相关性或干扰性。在我们看来，分析方法必须设计得与实验相匹配，这与DP中给出的建议相反。最后，我们强调了零假设检验的弱点以及p值无法预测结果是否具有普遍性或可重复性。
