Statistics matter greatly in biology, whether we like it or not. As a discipline with an empirical inclination, we are faced with data every day and we rely on inferential statistical models to make sense of it and to provide us with novel insights. Much of the time, the growing level of complexity and sophistication of the models we put to use in ecology and evolution have led to more appropriate analyses of our data. However, this is not always the case. Here, I draw attention to a classic flaw in inferential statistics that has resurfaced in a new flavor as a result of increased reliance on complex linear mixed models - the multifaceted and disturbingly persistent problem of pseudoreplication.

中文翻译：

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混合模型不提供自由度。

无论我们喜不喜欢，统计学对生物学都至关重要。作为一门经验丰富的学科，我们每天都要面对数据，我们依靠推理统计模型来理解数据并为我们提供新颖的见解。在很多时候，我们在生态学和进化论中使用的模型的复杂性和复杂性的水平不断提高，导致对我们的数据进行更适当的分析。然而，这并非总是如此。在此，我提请注意推理统计中的一个经典缺陷，由于对复杂线性混合模型的依赖性增加，这种缺陷又以一种新的形式浮出水面-伪复制的多方面且令人困扰的持久问题。