Doing Meta-Analysis with R: A Hands-On Introduction for Health Policy and Population Health Researchers (Intermediate; Added Fee)

This workshop introduces participants to the theory and practice of meta-analysis using the R programming environment. As evidence synthesis becomes increasingly central to health policy decision-making, population health research, and clinical guideline development, the ability to conduct transparent, reproducible, and statistically rigorous meta-analyses is an essential skill for modern researchers. The workshop is structured as a progressive, hands-on learning experience. Beginning with the foundational logic of evidence synthesis, participants will move through the full meta-analytic workflow — from formulating a structured research question and understanding study heterogeneity, to calculating effect sizes, fitting pooled models, and detecting publication bias — with each concept immediately applied in R. Emphasis is placed on interpretability, reproducibility, and adherence to current reporting standards (PRISMA 2020). All analyses will be conducted using the meta, metafor, and dmetar packages in R, which together provide a comprehensive and well-documented toolkit for meta-analytic work. Participants will work with real-world health and public health datasets to ensure that skills acquired are directly transferable to their own research. The workshop is designed to be accessible to those who are new to meta-analysis but already comfortable with basic R syntax. No prior experience with evidence synthesis methods is required. By the end of the session, participants will have run their first complete meta-analysis in R, including a forest plot and a publication bias assessment, and will leave with fully annotated R scripts they can adapt for their own work. Target Audience: Graduate Students, Early Career Researchers, Faculty, Public Health Practitioners