Meta-Analysis Forest Plot: Pooling Clinical Trials
Interactive 3D forest-plot simulator: pool effect sizes from simulated clinical trials with inverse-variance weighting, compare fixed-effect vs DerSimonian-Laird random-effects models, and watch the I² heterogeneity statistic respond live.
A meta-analysis combines the effect estimates of many independent clinical trials into one pooled number — the statistical backbone of evidence-based medicine. This simulator generates a cohort of simulated trials, each with its own sample size, standard error and observed log risk ratio, and renders them as a real 3D forest plot: box size shows each study's inverse-variance weight, whisker length shows its 95% confidence interval, and a red diamond at the front row shows the pooled estimate. Toggle between the fixed-effect and DerSimonian–Laird random-effects models, dial in the between-study heterogeneity, and watch the I² statistic, Q test and pooled confidence interval respond exactly as they would in a real Cochrane review.
Pool effect sizes from simulated clinical trials into a 3D forest plot, comparing fixed-effect inverse-variance weighting against DerSimonian-Laird random-effects pooling as the I² heterogeneity statistic responds live.
3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install