Analysts seldom include interaction terms in meta-regression model, what can introduce bias if an interaction is present. We illustrate this in the current paper by re-analyzing an example from research on acute heart failure, where neglecting an interaction might have led to erroneous inference and conclusions. Moreover, we perform a brief simulation study based on this example highlighting the effects caused by omitting or unnecessarily including interaction terms. Based on our results, we recommend to always include interaction terms in mixed-effects meta-regression models, when such interactions are plausible.
翻译:分析家很少在元回归模型中包括互动术语,如果存在互动,什么可以引入偏见。我们在本文件中通过重新分析急性心脏衰竭研究中的一个实例来说明这一点,因为忽视互动可能导致错误的推论和结论。此外,我们根据这个实例进行一个简短的模拟研究,强调忽略或不必要地包括互动术语所产生的影响。根据我们的结果,我们建议,在混合效应元回归模型中始终包括互动术语,如果这种互动是可信的。