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Bayesian approach for meta-analyses in biomedical research: a scoping review protocol
Joseph Alvin Santos1, Emilia Riggi2, Robert Grant3,4
1Department of Business Economics, Health and Social Care (DEASS), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Manno, Ticino, Switzerland.
This scoping review examines Bayesian methods in biomedical meta-analyses. Findings will inform best practices for using these advanced statistical techniques in research synthesis.
Area of Science:
- Biostatistics
- Biomedical Research
- Meta-Analysis
Background:
- Bayesian methods offer a flexible framework for meta-analysis, adept at handling complex and heterogeneous data.
- Despite increasing use in biomedical research, Bayesian methods are underutilized in meta-analyses.
- This review addresses the current scope and reporting of Bayesian meta-analyses.
Purpose of the Study:
- To describe and analyze the application and reporting of Bayesian methods in biomedical meta-analyses.
- To identify trends and gaps in the use of Bayesian approaches for evidence synthesis.
- To provide insights for researchers utilizing Bayesian meta-analysis.
Main Methods:
- Scoping review conducted following JBI methodology.
- Searches of PubMed, Embase, CINAHL, and Cochrane Library for papers published since 2016.
- Data extraction and analysis using frequency counts, narrative synthesis, and workflow mapping.
Main Results:
- The review will map the scope of Bayesian meta-analysis use in biomedical research.
- Analysis will identify common reporting practices and potential areas for improvement.
- Results will inform the development of an appropriate workflow for Bayesian meta-analyses.
Conclusions:
- The findings will highlight the current landscape of Bayesian meta-analysis in biomedicine.
- This review aims to guide researchers in the effective application and reporting of these methods.
- Recommendations will be provided to enhance the utilization of Bayesian approaches in meta-analysis.
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