Funnel Plot
Chart overview
Funnel plots display individual study effect estimates against a measure of precision (standard error or sample size), forming an inverted funnel shape when no publication bias is present.
Key points
- Systematic reviewers use asymmetry in the funnel to detect potential publication bias, small-study effects, or heterogeneity, often supplemented by Egger regression test.
- The plot is a required element in Cochrane systematic reviews and PRISMA-compliant meta-analyses.
Example Visualization
Create This Chart Now
Generate publication-ready funnel plots with AI in seconds. No coding required – just describe your data and let AI do the work.
View example prompt
"Create a funnel plot from my data. Plot effect size on the x-axis and standard error (inverted, small SE at top) on the y-axis. Draw pseudo 95% confidence funnel lines around the pooled estimate and add a vertical dashed line for the overall effect. Plot each study as a circle, scaled by inverse variance weight if available. Use journal formatting with Arial font and no top or right spines."
How to create this chart in 30 seconds
Upload Data
Drag & drop your Excel or CSV file. Plotivy securely processes it in your browser.
AI Generation
Our AI analyzes your data and generates the Funnel Plot code automatically.
Customize & Export
Tweak the design with natural language, then export as high-res PNG, SVG or PDF.
Python Code Example
Console Output
Figure saved: plotivy-funnel-plot.png
Common Use Cases
- 1Assessing publication bias in systematic reviews and meta-analyses of clinical trials
- 2Detecting small-study effects and heterogeneity in pharmacological intervention studies
- 3Evaluating reporting bias in diagnostic test accuracy meta-analyses
- 4Presenting Egger regression test results visually alongside statistical test output
Pro Tips
Invert the y-axis so studies with the smallest standard error appear at the top of the funnel
Draw 95% and 99% pseudo-confidence contour lines to distinguish random sampling variation from bias zones
Scale scatter point size by study weight to communicate relative contribution visually
Add a trim-and-fill adjusted estimate as a different marker shape to indicate corrected pooled effect
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.