Understanding Between-Study Heterogeneity in Meta-Analysis Research

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Between-study heterogeneity refers to the degree to which true effect sizes vary across studies within a meta-analysis, and quantifying it is essential for interpreting pooled results reliably. Cochran's Q, a weighted sum of squared deviations from the summary effect, has traditionally been used to measure this variance, though it is sensitive to the number of studies and their precision. Because Q's significance depends heavily on a meta-analysis's size and statistical power, researchers are cautioned against relying on it alone. The I² statistic, derived directly from Cochran's Q, addresses some of these limitations by expressing heterogeneity as a percentage of total variability not attributable to sampling error. Together, these tools help analysts assess whether a pooled effect estimate is meaningful or obscured by excessive variation across studies.

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