Forest plot & meta-analysis

Pool studies (fixed & random effects), funnel plot & Egger’s test.

Full guide →
Effect measure
Model
StudyEstimateLower 95%Upper 95%
Random-effects pooled estimate: 0.77 [0.68, 0.88] · I² = 0%, τ² = 0.000 · 5 studies
Your forest plot — updates live
Forest plotStudyEstimate [95% CI]WeightAbraham 20090.72 [0.51, 1.02]14.7%Bianchi 20120.65 [0.44, 0.96]11.6%Costa 20150.88 [0.70, 1.11]33.2%Devi 20170.55 [0.32, 0.94]6.1%Eriksson 20200.79 [0.63, 0.99]34.5%Overall (random-effects)0.77 [0.68, 0.88]100%0.51Heterogeneity: I² = 0%, τ² = 0.000, Q = 3.70 (df = 4)Generated free with Folio · usefolio.co

Enter each study’s effect estimate and 95% confidence interval. Standard errors are derived from the CIs; pooling uses inverse-variance weighting (fixed-effect and DerSimonian–Laird random-effects). Free — everything runs in your browser.

Writing the review?

Folio drafts with your own sources, checks every citation, and records a verifiable writing history — and pairs with our free PRISMA flow diagram generator.

Start writing free