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Is it time for the cochrane collaboration to reconsider its meta-analysis methodology?

机译：是时候Cochrane合作重新考虑其荟萃分析方法了吗？

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Meta-analysis is becoming more popular in the biomedical literature and of increasing importance to clinicians, policy makers, funding $bdies, and researchers for synthesizing practice guidelines, grant justification, and making policy decisions. Meta-analysis involves a quantitative analysis of multiple study outcomes to reach conclusions regarding an intervention. Often these studies are different in their design and conduct. One method of meta-analysis endorsed by the Cochrane Collaboration that has raised significant controversy is the random-effects model, which assumes that underlying effects vary across differing study populations. Often larger studies, even if not well designed and meticulously conducted, have more information value than smaller studies. The random effects model redistributes weights in one direction only—from big to small studies— without addressing variations in study estimate related to study quality and conduct. Finally, this estimator cannot be expected to have a variance structure that is different from that of the arithmetic mean when heterogeneity is large.
机译：元分析在生物医学文献中正变得越来越流行，并且对于临床医生，政策制定者，资助机构和研究人员来说，用于综合实践指南，批准理由和制定政策决策的重要性日益增加。荟萃分析涉及对多项研究结果的定量分析，以得出有关干预措施的结论。这些研究通常在设计和行为上有所不同。 Cochrane协作组织认可的一项荟萃​​分析方法引起了很大的争议，即随机效应模型，该模型假设基础效应在不同研究人群之间有所不同。通常，较大的研究，即使设计不当和精心进行，也比较小的研究具有更多的信息价值。随机效应模型仅在一个方向上（从大型研究到小型研究）重新分配权重，而没有解决与研究质量和行为有关的研究估计中的差异。最后，当异质性较大时，不能期望该估计器具有与算术平均值不同的方差结构。

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