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

By M. Borenstein, Julian P. T. Higgins, L. Hedges, H. Rothstein. Research Synthesis Methods, 2017

1,596 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/005bc2b51bd8838b2ea49b2418a19f4ad62d678e

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Citations in the corpus

A Meta-Analytic Review of the Relations Between Motivation and Reading Achievement for K–12 Students (2020, methodology): “As per recent recommendations related to reporting of heterogeneity in meta-analyses (see Borenstein et al., 2017), tau-squared (τ2) was used to calculate between-study variance sampling variance and assign study weights in the random-effects model. τ2 is an absolute measure of heterogeneity…”
Teacher Professional Development and Student Reading Achievement: A Meta-Analytic Review of the Effects (2019, background): “It allows us to make inferences about the distribution of effect sizes (Borenstein et al., 2017).”
Effective Programs in Elementary Mathematics: A Meta-Analysis (2021, methodology): “Benchmark assessments A major feature of the present review is its use of modern approaches to meta-analysis and meta-regression that enable researchers to control effects of programs, categories and variables for substantive and methodological factors, and to obtain meaningful estimates for key mod”
Evidence that organic farming promotes pest control (2018, background): “I ² is a percentage, which corresponds to the ratio between the variance explained by the true effect sizes and the observed variance 54 .”
Domain-specific prior knowledge and learning: A meta-analysis (2021, background): “The high heterogeneity index of I2 ¼ 96.93 indicated that a large proportion of the variance of effect sizes was due not to sampling error but to moderating influences of other variables (Borenstein et al., 2017).”
A systematic review and meta-regression of the prevalence and incidence of perinatal depression. (2017, methodology): “The I2 statistic was used as a measure of the proportion of the observed variance that is not due to sampling error (Borenstein et al., 2017)..”
How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses. (2019, neutral): “The Q statistic provides the standard significance test for between-study heterogeneity, and the T 2 statistic quantifies the amount of true heterogeneity between studies (Borenstein et al. 2009, 2017).”
Anonymity and Online Self-Disclosure: A Meta-Analysis (2019, methodology): “To answer RQ2, moderation subgroup analyses (Borenstein et al., 2017) were used to determine heterogeneity on the criteria set forth by the moderators.”
Global prevalence of gaming disorder: A systematic review and meta-analysis (2020, methodology): “  1 The degree of between-study heterogeneity, or the variance in prevalence estimate, was examined using the following two indices: Cochrane’s Q, which determines the ratio of observed variation to within-study error (Borenstein et al., 2017) and the I2 statistic, which estimates the true effect ”
Introduction, comparison, and validation of Meta‐Essentials: A free and simple tool for meta‐analysis (2017, methodology): “CMA provides a separate Excel workbook on its website to calculate prediction intervals based on CMA output.(40) effect size, CI (t distribution; KNHA), prediction interval, subgroup analysis, and meta‐regression (one covariate) were exactly equal (to at least 6 decimals).”
A Meta-Analysis of Negative Feedback on Intrinsic Motivation (2018, methodology): “In addition, we also calculated 95% prediction intervals (Borenstein et al. 2017), which indicates the range the effect size will fall in a given population drawing from the entire universe of studies.”