Abstract
Systematic review and meta-analyses (SRMA) form the cornerstone of evidence-based medicine and evidence-based public health. SRMA occupies the highest position in the evidence pyramid. Thus, researchers, clinicians, public health professionals, policymakers, and other stakeholders place much trust in the findings of an SRMA. So, these interpretations must be methodologically robust and statistically sound. No comprehensive and sound tutorial is available for meta-analysis of different effect sizes condensed in a single article. This is an easy yet comprehensive guide to fill this gap. It also incorporates some advanced but essential meta-analytical techniques. Everything has been explained simply in open-source and free software, i.e., R. This allows greater access by researchers from lower- and middle-income countries, ensuring inclusivity and equitable access to health research. Although the primary target readers are beginners of R, seasoned R users can also benefit from the advanced analyses introduced in the meta-analysis, thereby addressing the needs of both groups. It explains statistical concepts briefly as necessary and demonstrates their implementation. The code file for the demonstrated examples and the relevant data extraction sheets have been attached. Then, we have provided examples for reporting the results of a systematic review and meta-analysis, troubleshooting common mistakes, customising the output, changing the finer settings, and exploring other important aspects of meta-analysis. We have finally discussed other sources for further reading for those interested in delving into more advanced and complicated techniques.
Keywords:
Systematic review, Tutorial, Course, Step-by-step guide, Statistical analysis, R Studio, R Software, Troubleshooting, Funnel plot, Egger’s regression, Egger’s test, Doi plot, LFK index, Prediction interval, Heterogeneity, Bubble plot, Meta-regressionReferences
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