Abstract：
The purpose of many preclinical studies is to determine whether an experimental intervention affects an outcome through a particular mechanism, but the analytical methods and inferential logic typically used cannot answer this question, leading to erroneous conclusions about causal relationships, which can be highly reproducible. A causal mediation analysis can directly test whether a hypothesised mechanism is partly or completely responsible for a treatment\'s effect on an outcome. Such an analysis can be easily implemented with modern statistical software. We show how a mediation analysis can distinguish between three different causal relationships that are indistinguishable when using a standard analysis.
摘要：
许多临床前研究的目的是确定实验性干预是否通过特定机制影响结果。但是通常使用的分析方法和推理逻辑无法回答这个问题，导致关于因果关系的错误结论，这可以是高度可再现的。因果中介分析可以直接测试假设的机制是否部分或完全负责治疗对结果的影响。这种分析可以用现代统计软件容易地实现。我们展示了中介分析如何区分使用标准分析时无法区分的三种不同的因果关系。
