Effect size and CI for each study, plus a pooled diamond at the bottom.
A free, animated forest plot you can read here or embed on any website, from Scrollchart.
Forest Plot
A forest plot summarizes the results of multiple studies on the same question by showing each study's point estimate and confidence interval as a horizontal line with a weighted square at its center. The square's size encodes how much that study contributes to the overall pool: larger trials get larger squares. A vertical null line marks the value of no effect (relative risk 1.0 for ratio measures, 0 for mean differences). Studies whose confidence intervals cross the null are individually consistent with no effect.
At the bottom, a diamond represents the pooled effect from all studies combined. The diamond's center is the meta-analytic estimate and its width spans the pooled 95% confidence interval. If the diamond does not touch the null line, the pooled evidence favors an effect at p < 0.05.
Read each row top to bottom as a separate study. The further a square sits from the null line, the larger the effect in that study. Wide whiskers indicate a small sample or high variance; narrow whiskers indicate a large, precise study. A square to the right of the null line for a relative-risk plot means the treatment increased the outcome; to the left means it decreased it.
The pooled diamond is the key deliverable. Assess three things: (1) where the center sits relative to the null (direction of effect), (2) whether the diamond spans the null (statistical significance), and (3) the I-squared statistic, usually reported above or below, which quantifies what fraction of variation across studies reflects genuine heterogeneity rather than chance.
The term "forest plot" is sometimes attributed to Richard Peto's group at Oxford in the 1980s. The Cochrane Collaboration standardized the format through its RevMan software and Handbook methodology in the 1990s and 2000s. The I-squared statistic for quantifying heterogeneity was introduced by Higgins and Thompson in 2002, replacing the older Q-statistic which was sensitive to the number of studies. I-squared values above 50% are generally considered substantial heterogeneity; above 75% considerable.
For ratio outcomes (risk ratio, odds ratio, hazard ratio) the x-axis is plotted on a log scale so that symmetrical CI widths represent symmetric uncertainty on the ratio scale.
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Source & accuracy
This forest plot is an editorial illustration built to represent the concept accurately. Where it shows figures, they are typical or representative values chosen to make the relationship clear, not a single underlying dataset. The diagram and its explainer are reviewed and maintained centrally, and updated over time as understanding improves.
Individual studies and the pooled bottom line
Each horizontal line in a forest plot represents one study's effect estimate (the point) and confidence interval (the line width). Studies are stacked vertically, often sorted by precision or sample size. The diamond at the bottom pools all studies using meta-analytic methods, producing a narrower confidence interval than any single study because it harnesses combined sample size.
When individual study lines overlap substantially, heterogeneity is present; when they fan widely or include zero while the pooled diamond excludes it, the studies disagree. The pooled effect represents the average treatment benefit across the evidence base, weighted by study precision.
Interpreting overlap and consistency
A forest plot where all confidence intervals nest together and the pooled effect is narrow suggests homogeneous findings and robust conclusions. Scatter across a wide range (some favoring treatment, others favoring control) suggests heterogeneity, warranting subgroup or meta-regression analysis to understand what divides the findings.
A study with a massively wide confidence interval (small sample) contributes little to the pooled estimate; conversely, a large trial narrows its band and pulls the overall diamond toward its result. Reading this visual grammar reveals how much each study shaped the final answer.
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Reference
What this is
A free, embeddable, animated forest plot for any website.
Who uses it
Researchers & academics, Science journalists, Medical educators, Health journalists.
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License
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Frequently asked questions
Where can I get a free animated "Forest Plot" for my website?
Scrollchart provides "Forest Plot" as a free, embeddable animated diagram you can add to any website with one line of HTML. No signup is required and there is no watermark. The diagram and its explainer text are served from scrollchart.com, so the embed stays current without any maintenance on your end.
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