Glossary // Glossary term Technical
Heterogeneity (I²)
Variation in results between studies in a meta-analysis beyond what chance alone would produce, reflecting differences in populations, interventions, measures or study quality. The I² statistic, proposed by Higgins and Thompson, describes the proportion of total variation in study estimates that is due to heterogeneity rather than sampling error, independently of the number of studies and the effect metric. High heterogeneity means a pooled average may describe few real settings well, so moderators and the spread of effects matter as much as the mean. How one could reason about recording a catharsis-like change of state: signals, features, inference and context, baselines, self-report, error costs and ethics, and why every step stays uncertain. Nothing on this site measures anyone. Every public claim on this site with its type, evidence level, confidence, sources and review date, and an appraisal of each reference. How claims are graded, how art is kept apart from evidence, and how to report a problem. The works the definition rests on, with the level of evidence each was appraised at. (2002). Quantifying heterogeneity in a meta-analysis. doi:10.1002/sim.1186 Supports the definition of I² as the proportion of total variation in study estimates due to heterogeneity, independent of the number of studies and the effect metric. Methods guidance, not evidence about any emotional outcome.Where the site uses it
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