Quantitative synthesis: a practical guide on meta-analysis, meta-regression, and publication bias tests for environmental sciences
This is a step-by-step tutorial, which is a supplement to our methodological guideline paper written for Environmental Evidence (the official journal of the Collaboration for Environmental Evidence (CEE)).
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Our target audience is broad, and includes beginners and students to senior researchers who might have already conducted meta-analyses in environmental sciences.
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While the material covered is mostly relevant to researchers from environmental sciences, the tutorial should be accessible to meta-analysts from other disciplines.
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In addition to detailed instructions and well-annoted scripts for implementing and interpreting the analyses using the R software environment, we also provide details of the underlying math and statistical theory to enable readers to implement these methods using other statistical software (e.g.,
Python,Stata). -
The tutorial will be updated when necessary. Readers can access the latest version in our GitHub repository .
This online tutorial has borrowed ideas and code from published papers in Prof. Shinichi Nakagawa's lab (see full publication list) and from (Associate) Prof. Wolfgang Viechtbauer's versatile R package metafor (see the documentation, GitHub page, and package webpage).
We thank the these two research groups for their advocacy of Open Science practices. We encourage the researchers from all fields to embrace open, reliable, and transparent practices, such as thorugh sharing data and code, transparent reporting and archiving.
If our paper and tutorial have helped you, please cite the following paper (preprint):
Shinichi Nakagawa, Yefeng Yang, Erin Macartney, Rebecca Spake, and Malgorzata Lagisz. Quantitative synthesis: a practical guide on meta-analysis, meta-regression, and publication bias tests for environmental sciences. Environmental Evidence 12, Article number: 8 (2023) [Link]