Meta-analysis

A meta-analysis statistically combines the results of several studies addressing the same question to produce a single pooled estimate of effect, usually with a confidence interval. Pooling increases the effective sample size, which can sharpen precision and detect effects too small for individual studies to confirm. It is often the quantitative step within a systematic review. The method does not fix flawed inputs: combining biased or poorly designed studies yields a precise-looking but misleading answer, sometimes called garbage in, garbage out. When reading a meta-analysis, check how consistent the individual studies were (heterogeneity), whether small or negative studies may be missing (publication bias), and whether the pooled studies were similar enough to combine sensibly. A forest plot helps: it shows each study's estimate and the pooled result, letting you see whether studies agree. For example, pooling ten small trials of a drug may reveal a modest benefit that no single underpowered trial could establish on its own.