Forest plot maker
Upload your effect sizes and confidence intervals and get a clean forest plot — per-study estimates, weights, and a pooled diamond — ready for a systematic review.
Why use it
Meta-analysis ready
Per-study point estimates with confidence intervals, study weights, and a pooled summary diamond, laid out the way journals expect.
No coding
Skip the metafor/R boilerplate — provide your table and describe the plot in plain language.
Publication-grade export
Editable SVG and high-DPI PDF/PNG for your manuscript.
How it works
Upload your studies
Provide a table of study names with effect sizes (OR, RR, HR, or mean difference) and confidence intervals.
Configure the plot
Set the effect measure, add weights, a reference line, and a pooled estimate.
Export the figure
Download a publication-ready SVG/PDF, or refine labels and scale first.
What you can do with it
Systematic reviews
Summarize effects across included studies in one figure.
Clinical meta-analysis
Pool odds ratios or hazard ratios with confidence intervals.
Subgroup comparisons
Show effects across subgroups with a clear reference line.
Frequently asked questions
What data does a forest plot need?
A table of studies with an effect size (odds ratio, risk ratio, hazard ratio, or mean difference) and its confidence interval; optionally study weights.
Can it show a pooled estimate?
Yes — add a pooled summary diamond and a reference line for the null effect.
Do I need R or metafor?
No — the forest plot maker is no-code; upload your table and describe the figure in plain language.
Is it publication-ready?
Yes — journal-grade styling with editable SVG and high-DPI PDF/PNG/EPS export.
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