A meta-analysis is a statistical method used to systematically combine quantitative data from multiple independent studies that address a common research question. By extracting and synthesizing effect sizes and variance measures from these studies, meta-analysis produces a single, more precise estimate of the effect being studied, improving statistical power and helping to resolve inconsistencies among individual study results
. It is typically part of a broader systematic review, which involves a comprehensive and unbiased search for all relevant studies meeting predefined criteria. While systematic reviews summarize and assess the evidence qualitatively, meta-analyses quantitatively integrate the data to generate a combined effect size
. Key features of meta-analysis include:
- Combining summary results (not individual participant data) from selected studies
- Increasing precision in estimating treatment effects or associations by pooling data
- Assessing heterogeneity among study results to understand variations and guide further research
- Providing transparent and reproducible synthesis to minimize bias compared to narrative reviews
Meta-analyses are widely used in health research to inform clinical guidelines, policy decisions, and future research directions by consolidating evidence from multiple studies
