Basics of meta-analysis: I2 is not an absolute measure of heterogeneity

Michael Borenstein*, Julian P.T. Higgins, Larry V. Hedges, Hannah R. Rothstein

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

969 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)5-18
Number of pages14
JournalResearch synthesis methods
Issue number1
StatePublished - Mar 1 2017


  • I
  • I-squared
  • I2
  • heterogeneity
  • inconsistency
  • meta-analysis
  • prediction intervals

ASJC Scopus subject areas

  • Education


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