metaanalize
Meta-analyze, or to conduct a meta-analysis, is a statistical method used to combine results from multiple independent studies addressing the same question to derive a pooled estimate of effect. The approach aims to increase statistical power, improve estimates of the effect size, and resolve uncertainty when individual studies report varying results. In practice, researchers define a research question and eligibility criteria, conduct a systematic literature search, select studies, extract data on outcomes and study characteristics, and compute study-level effect sizes (e.g., odds ratios, risk ratios, mean differences). These effects are then synthesized using fixed-effect models, which assume a common true effect, or random-effects models, which allow for between-study variation. Heterogeneity is assessed with statistics such as Q and I^2, and sources of heterogeneity may be explored via subgroup analyses or meta-regression. Publication bias is considered through funnel plots and tests like Egger’s or Begg’s, acknowledging that non-reporting of negative results can bias the pooled estimate. Meta-analyses may also involve quality assessment of included studies, sensitivity analyses, and sometimes the use of Bayesian methods.
Interpretation focuses on the magnitude and precision of the pooled effect, consistency across studies, and the