What is between-study heterogeneity in meta-analysis, and what does the I^2 statistic represent?

What is between-study heterogeneity in meta-analysis, and what does the I^2 statistic represent?

• A. Variation in effect estimates beyond chance; I^2 quantifies proportion due to heterogeneity.
• B. Heterogeneity is variation within a study; I^2 measures study quality.
• C. Heterogeneity is the average effect; I^2 measures publication bias.
• D. It measures overall sample size; I^2 is a p-value.

Answer: (A)

Between-study heterogeneity in meta-analysis refers to the variability in effect estimates across different studies that cannot be explained by random sampling error alone. The I^2 statistic quantifies how much of the observed variation among study results is due to true differences in effect sizes (heterogeneity) rather than chance. It is expressed as a percentage from 0% (no heterogeneity) to 100% (all variability due to heterogeneity). This measure is about differences between studies, not variation within a single study, not study quality, not the overall average effect, and not a p-value or publication bias.

Between-study heterogeneity in meta-analysis refers to the variability in effect estimates across different studies that cannot be explained by random sampling error alone. The I^2 statistic quantifies how much of the observed variation among study results is due to true differences in effect sizes (heterogeneity) rather than chance. It is expressed as a percentage from 0% (no heterogeneity) to 100% (all variability due to heterogeneity). This measure is about differences between studies, not variation within a single study, not study quality, not the overall average effect, and not a p-value or publication bias.