BioStat, Inc., Englewood, NJ, USA.
School of Social and Community Medicine, University of Bristol, Bristol, UK.
Res Synth Methods. 2017 Mar;8(1):5-18. doi: 10.1002/jrsm.1230. Epub 2017 Jan 6.
When we speak about heterogeneity in a meta-analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of the intervention. While there is a common belief that the I statistic provides this information, it actually does not. In this example, if we are told that I is 50%, we have no way of knowing if the effects range from 40 to 60, or from 10 to 90, or across some other range. Rather, if we want to communicate the predicted range of effects, then we should simply report this range. This gives readers the information they think is being captured by I and does so in a way that is concise and unambiguous. Copyright © 2017 John Wiley & Sons, Ltd.
当我们在荟萃分析中提到异质性时，我们的目的通常是理解异质性的实质性含义。如果一项干预措施产生的平均效应大小为 50 分，我们想知道在不同人群中，效应大小的差异是在 40 到 60 之间，还是在 10 到 90 之间，因为这关系到干预措施的潜在效用。虽然人们普遍认为 I 统计量提供了这些信息，但实际上并非如此。在这个例子中，如果我们被告知 I 是 50%，我们无法知道效应的范围是在 40 到 60 之间，还是在 10 到 90 之间，或者在其他范围内。相反，如果我们想传达预测的效应范围，那么我们应该直接报告这个范围。这为读者提供了他们认为 I 所捕捉到的信息，并且以简洁明了的方式做到了这一点。版权所有 © 2017 约翰威立父子有限公司。
