What is meta-analysis and how to conduct meta-analysis in research?

Meta-analysis is a statistical method that systematically combines quantitative data from multiple independent studies on the same research question to derive an overall estimate of effect or association. It provides a rigorous synthesis of existing evidence. Conducting a meta-analysis requires a predefined protocol outlining inclusion criteria, search strategies, and analysis plans. Key principles include comprehensive and systematic literature searching to minimize bias, rigorous assessment of included study quality and risk of bias (e.g., using tools like ROB-2), quantitative data extraction, and careful evaluation of statistical heterogeneity among studies (e.g., using I² statistic). Appropriate statistical models (fixed-effect or random-effects) must be selected based on heterogeneity. Implementation steps involve: (1) defining a precise research question using PICO/PECO frameworks; (2) executing a systematic literature search in multiple databases; (3) screening studies and applying eligibility criteria; (4) extracting relevant effect size data consistently; (5) statistically pooling results and exploring heterogeneity; and (6) interpreting findings, acknowledging limitations (like publication bias), and reporting rigorously (e.g., PRISMA guidelines). It is widely applied in medicine, social sciences, and education to inform practice and policy.