Quantifying heterogeneity in a meta‐analysis
By Julian P. T. Higgins, S. Thompson. Statistics in Medicine, 2002
32,761 citations recorded by the source corpus.
Subfields: Statistics and Probability, Surgery
View Paper: https://www.semanticscholar.org/paper/d76bde423b71f1cb900b988311bd2d71b700d506
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- John P. A. Ioannidis
- Julian P. T. Higgins
- Georgia Salanti
- Douglas G. Altman
- David Moher
- Ian R. White
- Mike W.-L. Cheung
- Dan Jackson
In Surgery
- Paul T. von Hippel
- John P. A. Ioannidis
- Ian R. White
- S. Thompson
- A. Vedel
- Georgia Salanti
- Julian P. T. Higgins
- F. B. Hu
Citations in the corpus
- Non-alcoholic fatty liver disease and risk of incident cardiovascular disease: A meta-analysis. (2016, neutral): “and approximately 75% represent high heterogeneity [18].”
- Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis (2019, methodology): “When using the true study-specific sample means and standard deviations, I(2) 1⁄4 98:15%.(31) The Luo/Wan, QE, and BC methods yielded similar estimates of I(2); using 98:15% as the true value of I(2), all three methods had relative errors between 0:02 and 0:02 for estimating I(2) in S1, S2, and S3.”
- Does job crafting always lead to employee well-being and performance? Meta-analytical evidence on the moderating role of societal culture (2020, methodology): “Thus, we used Hedges’ Q-test of homogeneity (Hedges & Olkin, 1985) and the I2 measure of relative heterogeneity (Higgins & Thompson, 2002), where a significant Q-test and high values of I2 suggest the presence of moderators, such as study characteristics (Higgins & Thompson, 2002).”
- Computer-delivered interventions for health promotion and behavioral risk reduction: a meta-analysis of 75 randomized controlled trials, 1988-2007. (2008, methodology): “To further assess heterogeneity, the I 2 index and its 95% confidence intervals were calculated to assess the inconsistencies in a set of effect sizes (Higgins and Thompson 2002; Huedo-Medina et al. 2006).”
- Success of fishmeal replacement through poultry by‐product meal in aquaculture feed formulations: a meta‐analysis (2019, methodology): “Sensitivity analysis was done using the leave-one-out study analysis, which allows for the comparisons of between-study heterogeneity (I2; Higgins & Thompson 2002) with and without individual studies to determine their influence on effect sizes (Nakagawa et al. 2017).”
- Aortic stenosis in the elderly: disease prevalence and number of candidates for transcatheter aortic valve replacement: a meta-analysis and modeling study. (2013, neutral): “from the inverse variance fixed-effect model (8).”
- Global burden of COPD: systematic review and meta-analysis (2006, methodology): “Within-group heterogeneity was evaluated using Cochran’s Chi-squared test (also called the Q test) [14] and the I-squared statistic [ 15 ].”