Beyond Cochrane’s I²: Diverse Methods for Assessing Heterogeneity in Meta-Analysis

Authors

  • Abdullah Ashraf Hamad Faculty of Medicine, Menoufia University, Menoufia, Egypt. Medical Research Group of Egypt, Negida Academy, Arlington, MA, USA
  • Ibraheem M Alkhawaldeh Faculty of Medicine, Mutah University, Al-Karak, Jordan

DOI:

https://doi.org/10.62438/tunismed.v102i12.5561

Keywords:

Heterogeneity, Meta-Analysis, Cochrane

Abstract

Not applicable

Downloads

Download data is not yet available.

References

CHERIF H, DZIRI C.We need a Prediction Interval to evaluate the heterogeneity of meta-analyses. Tunis Med.

Hamad AA, Alkhawaldeh IM, Abbas A, et al. Incidence and risk factors of venous thromboembolism in patients with amyotrophic lateral sclerosis: a systematic review and meta-analysis. Tunis Med 2024; 102: 610–615.

Dziri C. How to assess heterogeneity for a meta-analysis? Tunis Med 2022; 100: 353-undefined.

Dwivedi SN. Which is the Preferred Measure of Heterogeneity in Meta-Analysis and Why? A Revisit. Biostat Biometrics Open Access J 2017; 1.. DOI: 10.19080/BBOAJ.2017.01.555555.

Higgins JPT. Measuring inconsistency in meta-analyses. BMJ 2003; 327.. DOI: 10.1136/bmj.327.7414.557.

Cochran WG. The Combination of Estimates from Different Experiments. Biometrics 1954; 10. DOI: 10.2307/3001666.

Borenstein M, Higgins JPT, Hedges L V., et al. Basics of meta‐analysis: I 2 is not an absolute measure of heterogeneity. Res Synth Methods 2017; 8. DOI: 10.1002/jrsm.1230.

Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta‐analysis. Stat Med 2002; 21. DOI: 10.1002/sim.1186.

Additional Files

Published

2024-12-01

Issue

Vol. 102 No. 12 (2024): Tunis Med dec 2024

Section

Author's response to letter to the editor

Categories

License

Copyright (c) 2024 La Tunisie Médicale

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.