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.
// anyplot.ai
// funnel-meta-analysis: Meta-Analysis Funnel Plot for Publication Bias
// Library: chartjs 4.4.7 | JavaScript 22.22.3
// Quality: 89/100 | Created: 2026-06-10
//# anyplot-orientation: landscape
const t = window.ANYPLOT_TOKENS;
// 15 RCTs comparing drug vs placebo — log odds ratios and standard errors
const studies = [
{ logOR: 0.52, se: 0.18 },
{ logOR: 0.41, se: 0.22 },
{ logOR: 0.28, se: 0.31 },
{ logOR: 0.35, se: 0.14 },
{ logOR: 0.18, se: 0.25 },
{ logOR: 0.60, se: 0.38 },
{ logOR: 0.45, se: 0.12 },
{ logOR: 0.22, se: 0.28 },
{ logOR: -0.05, se: 0.42 },
{ logOR: 0.38, se: 0.16 },
{ logOR: 0.55, se: 0.34 },
{ logOR: 0.30, se: 0.20 },
{ logOR: 0.48, se: 0.45 },
{ logOR: 0.15, se: 0.37 },
{ logOR: 0.62, se: 0.11 },
];
// Inverse-variance weighted pooled effect
const weights = studies.map(s => 1 / (s.se * s.se));
const totalWeight = weights.reduce((a, b) => a + b, 0);
const summaryEffect = studies.reduce((sum, s, i) => sum + weights[i] * s.logOR, 0) / totalWeight;
const maxSE = Math.max(...studies.map(s => s.se)) * 1.15;
const axisMax = Math.ceil(maxSE * 10) / 10; // round up to avoid duplicate boundary tick at 0.5
// Funnel boundaries: apex at (summaryEffect, 0), base at SE=maxSE
const funnelLeft = [{ x: summaryEffect, y: 0 }, { x: summaryEffect - 1.96 * maxSE, y: maxSE }];
const funnelRight = [{ x: summaryEffect, y: 0 }, { x: summaryEffect + 1.96 * maxSE, y: maxSE }];
// Mount canvas
const canvas = document.createElement("canvas");
document.getElementById("container").appendChild(canvas);
new Chart(canvas, {
type: "scatter",
data: {
datasets: [
// Funnel left boundary — in legend as "95% CI", fills toward right boundary
{
type: "line",
label: "95% Confidence Interval",
data: funnelLeft,
borderColor: t.palette[1],
backgroundColor: t.palette[1] + "26",
borderWidth: 2,
borderDash: [8, 5],
pointRadius: 0,
tension: 0,
fill: "+1",
},
// Funnel right boundary — hidden from legend, fill target for left boundary
{
type: "line",
label: "_funnel_right",
data: funnelRight,
borderColor: t.palette[1],
backgroundColor: "transparent",
borderWidth: 2,
borderDash: [8, 5],
pointRadius: 0,
tension: 0,
fill: false,
},
// Pooled effect vertical line
{
type: "line",
label: `Pooled effect (${summaryEffect.toFixed(2)})`,
data: [{ x: summaryEffect, y: 0 }, { x: summaryEffect, y: maxSE }],
borderColor: t.palette[0],
backgroundColor: "transparent",
borderWidth: 2.5,
pointRadius: 0,
tension: 0,
},
// Null effect reference line
{
type: "line",
label: "Null effect (0)",
data: [{ x: 0, y: 0 }, { x: 0, y: maxSE }],
borderColor: t.inkSoft,
backgroundColor: "transparent",
borderWidth: 1.5,
borderDash: [4, 4],
pointRadius: 0,
tension: 0,
},
// Individual study points — Imprint palette position 1 as first series
{
type: "scatter",
label: "Studies",
data: studies.map(s => ({ x: s.logOR, y: s.se })),
backgroundColor: t.palette[0] + "CC",
borderColor: t.pageBg,
borderWidth: 2,
pointRadius: 9,
pointHoverRadius: 11,
},
],
},
options: {
responsive: true,
maintainAspectRatio: false,
animation: false,
layout: { padding: { top: 10, right: 40, bottom: 10, left: 10 } },
plugins: {
title: {
display: true,
text: "funnel-meta-analysis · javascript · chartjs · anyplot.ai",
color: t.ink,
font: { size: 22, weight: "600" },
padding: { top: 16, bottom: 20 },
},
legend: {
display: true,
position: "bottom",
labels: {
color: t.inkSoft,
font: { size: 14 },
padding: 24,
usePointStyle: true,
filter: item => !item.text.startsWith("_"),
},
},
},
scales: {
x: {
title: {
display: true,
text: "Log Odds Ratio",
color: t.ink,
font: { size: 16, weight: "500" },
padding: { top: 10 },
},
ticks: { color: t.inkSoft, font: { size: 13 } },
grid: { color: t.grid },
border: { display: false },
},
y: {
reverse: true,
min: 0,
max: axisMax,
title: {
display: true,
text: "Standard Error",
color: t.ink,
font: { size: 16, weight: "500" },
},
ticks: { color: t.inkSoft, font: { size: 13 } },
grid: { color: t.grid },
border: { display: false },
},
},
},
});
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/funnel-meta-analysis/chartjs/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "funnel-meta-analysis",
"language": "javascript",
"library": "chartjs",
"page": "https://anyplot.ai/funnel-meta-analysis/javascript/chartjs",
"hub": "https://anyplot.ai/funnel-meta-analysis",
"code_json": "https://api.anyplot.ai/specs/funnel-meta-analysis/chartjs/code",
"spec_json": "https://api.anyplot.ai/specs/funnel-meta-analysis",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/chartjs/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/chartjs/plot-dark.png",
"interactive_light_html": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/chartjs/plot-light.html",
"interactive_dark_html": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/chartjs/plot-dark.html",
"quality_score": 89.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Meta-Analysis Funnel Plot for Publication Bias on anyplot.ai.