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Last Updated on October 14, 2026
Systematic review and meta-analysis techniques produce precise estimates of empirical studies to address issues that are pertinent for policy, practice, and future study. The application can also reveal unnoticed patterns in the results of previous studies, producing new insights. For these reasons, there has been an increase in the use of systematic reviews and meta-analyses in the social, medical, and natural sciences.
Hosted by Dahdaleh faculty fellow Godfred Boateng and facilitated by Dr. Reginald Quansah, this four-day course discusses the fundamentals methods in systematic reviews and meta-analysis. It includes a series of lectures, exercises, group discussions, and supervised statistical training sessions.
This is a non-degree course is appropriate for graduate students, post-doctoral fellows, faculty, and senior researchers who have interest in evidence synthesis. Participants should have completed introductory courses in research methods and statistics.
Learning Objectives
Systematic review and meta-analysis method research is extremely useful in the era where a huge amount of research is produced each year, often with conflicting findings. In those instances, it can offer scientifically sound and powerful alternatives that can overcome the difficulties in addressing bias, heterogeneity and quality of the studies. However, often a poorly conducted systematic review and meta-analysis could yield misleading results. Therefore, various guidelines have been suggested to help standardized the independent study findings and to improve quality research.
In this course, participants gain a better understanding of systematic review and meta-analysis and gain the following skills:
- Recognize features of systematic reviews and meta-analyses as a research design
- Identify the elements of a well-defined review question
- Understand and develop search strategies
- Perform a comprehensive search for relevant studies
- Manage the results of systematic searches
- Extract data and assess risk of bias of included studies
- Understand and carry out quantitative analysis of extracted data
- Apply the methodology and conduct reviews independently
A certificate will be issued upon completion.
Themes | Global Health Foresighting |
Status | Active |
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