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Basics of meta-analysis: I2 is not an absolute measure of heterogeneity.
Research Synthesis Methods ( IF 5.0 ) Pub Date : 2017-01-06 , DOI: 10.1002/jrsm.1230
Michael Borenstein 1 , Julian P T Higgins 2 , Larry V Hedges 3 , Hannah R Rothstein 4
Affiliation  

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 I2 statistic provides this information, it actually does not. In this example, if we are told that I2 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 I2 and does so in a way that is concise and unambiguous. Copyright © 2017 John Wiley & Sons, Ltd.

中文翻译:

荟萃分析的基础:I2并非绝对的异质性度量。

当我们在荟萃分析中谈到异质性时,我们的目的通常是了解异质性的实质含义。如果一项干预措施产生的平均影响大小为50分,我们想知道不同人群的影响大小是从40到60,还是从10到90,因为这表明了该干预措施的潜在效用。尽管人们普遍认为I 2统计信息提供了此信息,但实际上却没有。在这个例子中,如果我们被告知2是50%,我们无法知道影响范围是40到60,还是10到90,还是其他范围。相反,如果我们想传达预期的影响范围,则我们只需报告此范围即可。这为读者提供了他们认为被I 2捕获的信息,并且这样做的方式简洁明了。版权所有©2017 John Wiley&Sons,Ltd.
更新日期:2017-01-06
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