The selection of appropriate statistical models for traditional meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

 ZHANG Tiansong

Jing’an District Central Hospital, Shanghai 200040, P.R.China;

Corresponding?author：

ZHANG Tiansong, Email: zhangtiansong@fudan.edu.cn

Keywords：

Meta-analysis; Statistical model; Common-effect; Fixed-effect; Random-effect

DOI：

10.7507/1672-2531.202008152

Video：

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Meta-analysis is the quantitative, scientific synthesis of research results. Fixed-effect and random-effect models are two popular statistical models for meta-analysis. The selection of the appropriate model is crucial. In this paper, we introduce some noval views of models and explain key assumptions, hypothesis, and interpretation of each model. We conclude with a discussion of factors to consider in model selection, and provide a recommendation on selection of appropriate statistical models for traditional meta-analysis.

Citation： ZHANG Tiansong. The selection of appropriate statistical models for traditional meta-analysis. Chinese Journal of Evidence-Based Medicine, 2020, 20(12): 1477-1481. doi: 10.7507/1672-2531.202008152 Copy

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1. Gurevitch J, Koricheva J, Nakagawa S, et al. Meta-analysis and the science of research synthesis. Nature, 2018, 555(7695): 175-182.
2. 張天嵩, 孫鳳, 董圣杰, 等. 網絡 Meta 分析統計模型及模型擬合軟件選擇. 中國循證心血管雜志, 2020, 12(7): 769-774, 793.
3. Borenstein M, Hedges LV, Higgins JP, et al. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods, 2010, 1(2): 97-111.
4. Riley RD, Higgins JPT, Deeks J. Interpretation of random effects meta-analysis. BMJ, 2011, 342: d549.
5. Deeks JJ, Higgins JPT, Altman DG. Chapter 10: Analysing data and undertaking meta-analyses. In: Higgins JPT, Thomas J, Chandler J, et al (editors). Cochrane handbook for systematic reviews of interventions (version 6.0, updated July 2019). Available at: www.training.cochrane.org/handbook.
6. Nikolakopoulou A, Mavridis D, Salanti G. Demystifying fixed and random effects meta-analysis. Evid Based Ment Health, 2014, 17(2): 53-57.
7. Nikolakopoulou A, Mavridis D, Salanti G. How to interpret meta-analysis models: fixed effect and random effects meta-analyses. Evid Based Ment Health, 2014, 17(2): 64.
8. Bender R, Friede T, Koch A, et al. Methods for evidence synthesis in the case of very few studies. Res Synth Methods, 2018, 9(3): 382-392.
9. Rice K, Higgins JPT, Lumley TS. A re-evaluation of fixed effect(s) meta-analysis. J R Stat Soc A, 2018, 181(1): 205-227.
10. Meta-analysis, 2020-8-26. Available at: https://www.stata.com/new-in-stata/meta-analysis/.
11. Murad MH, Montori VM, Ioannidis JPA, et al. Fixed-effects and random-effects models. In: Guyatt G, Rennie D, Meade MO, et al (Senior Editors). Users’ guide to the medical literature. A manual for evidence-based clinical practice (3rd ed). New York: McGraw-Hill, 2015.
12. Tufanaru C, Munn Z, Stephenson M, et al. Fixed or random effects meta-analysis? Common methodological issues in systematic reviews of effectiveness. Int J Evid Based Healthc, 2015, 13(3): 196-207.
13. Higgins JPT, Thompson SG, Spiegelhalter DJ. A re-evaluation of random-effects meta-analysis. J R Stat Soc Ser A Stat Soc, 2009, 172(1): 137-159.
14. Li J, Zhang Q, Zhang M, et al. Intravenous magnesium for acute myocardial infarction. Cochrane Database Syst Rev, 2007, (2): CD002755.
15. Gudmund R, Gergen M, 著. 吳喜之, 程博, 柳林旭, 等, 譯. 統計學. 北京: 高等教育出版社, 海德堡: 施普林格出版社, 2000: 147-166.

Chinese Journal of Evidence-Based Medicine

The selection of appropriate statistical models for traditional meta-analysis

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