Meta-Analysis Funnel Plot for Publication Bias in Python, R, Julia and JavaScript

Source code in 15 libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts.

A funnel plot used in meta-analysis to assess publication bias by plotting individual study effect sizes against their precision (typically standard error). Studies scatter around a summary effect line, with pseudo 95% confidence limits forming an inverted funnel shape. In the absence of bias, studies distribute symmetrically around the summary effect; asymmetry suggests publication bias or systematic heterogeneity. This is a standard tool in systematic reviews and Cochrane-style meta-analyses.

Renders

• Full-resolution render, light theme
• Full-resolution render, dark theme

Preview render from the Matplotlib implementation.

Implementations

• Meta-Analysis Funnel Plot for Publication Bias in Altair (Python)
• Meta-Analysis Funnel Plot for Publication Bias in Bokeh (Python)
• Meta-Analysis Funnel Plot for Publication Bias in lets-plot (Python)
• Meta-Analysis Funnel Plot for Publication Bias in Matplotlib (Python)
• Meta-Analysis Funnel Plot for Publication Bias in Plotly (Python)
• Meta-Analysis Funnel Plot for Publication Bias in plotnine (Python)
• Meta-Analysis Funnel Plot for Publication Bias in Pygal (Python)
• Meta-Analysis Funnel Plot for Publication Bias in Seaborn (Python)
• Meta-Analysis Funnel Plot for Publication Bias in ggplot2 (R)
• Meta-Analysis Funnel Plot for Publication Bias in Makie.jl (Julia)
• Meta-Analysis Funnel Plot for Publication Bias in Chart.js (JavaScript)
• Meta-Analysis Funnel Plot for Publication Bias in D3.js (JavaScript)
• Meta-Analysis Funnel Plot for Publication Bias in Apache ECharts (JavaScript)
• Meta-Analysis Funnel Plot for Publication Bias in Highcharts (JavaScript)
• Meta-Analysis Funnel Plot for Publication Bias in MUI X Charts (JavaScript)