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: echarts 5.5.1 | JavaScript 22.22.3
// Quality: 90/100 | Created: 2026-06-10
//# anyplot-orientation: landscape
const t = window.ANYPLOT_TOKENS;
// --- Data -------------------------------------------------------------------
// 18 RCTs comparing drug vs. placebo: log odds ratios and standard errors
const studyData = [
[-0.41, 0.08], [-0.52, 0.09], [-0.44, 0.12], [-0.55, 0.13],
[-0.39, 0.15], [-0.28, 0.16], [-0.48, 0.18], [-0.62, 0.20],
[-0.35, 0.22], [-0.58, 0.25], [-0.33, 0.28], [-0.71, 0.30],
[-0.19, 0.31], [-0.27, 0.35], [-0.12, 0.38], [-0.65, 0.40],
[-0.22, 0.43], [-0.50, 0.45],
];
const summaryEffect = -0.43;
const maxSE = 0.52;
const boundLeft = summaryEffect - 1.96 * maxSE; // ≈ −1.449
const boundRight = summaryEffect + 1.96 * maxSE; // ≈ 0.589
// Precision weights for symbol sizing (inverse variance)
const weights = studyData.map(([, se]) => 1 / (se * se));
const wMin = Math.min(...weights);
const wMax = Math.max(...weights);
// --- Init -------------------------------------------------------------------
const chart = echarts.init(document.getElementById("container"));
// --- Option -----------------------------------------------------------------
chart.setOption({
animation: false,
color: t.palette,
backgroundColor: "transparent",
title: {
text: "funnel-meta-analysis · javascript · echarts · anyplot.ai",
subtext: "Drug vs. Placebo RCTs — 18 studies",
left: "center",
top: 18,
textStyle: { color: t.ink, fontSize: 22, fontWeight: "bold" },
subtextStyle: { color: t.inkSoft, fontSize: 14 },
},
legend: {
data: [
{ name: "Studies", icon: "circle" },
{ name: "Summary effect (−0.43)", icon: "line" },
{ name: "95% CI bounds", icon: "line" },
{ name: "Null effect (0)", icon: "line" },
],
bottom: 20,
left: "center",
itemWidth: 22,
itemHeight: 14,
textStyle: { color: t.inkSoft, fontSize: 13 },
},
tooltip: {
trigger: "item",
backgroundColor: t.elevatedBg,
borderColor: t.inkSoft,
textStyle: { color: t.ink, fontSize: 13 },
formatter: params => {
if (params.seriesName !== "Studies") return "";
const [es, se] = params.data;
return `Study ${params.dataIndex + 1}<br/>LOR: ${es.toFixed(3)}<br/>SE: ${se.toFixed(3)}`;
},
},
grid: { left: 100, right: 70, top: 115, bottom: 110 },
xAxis: {
type: "value",
name: "Log Odds Ratio",
nameLocation: "center",
nameGap: 45,
nameTextStyle: { color: t.inkSoft, fontSize: 14 },
min: -1.7,
max: 0.8,
axisLabel: { color: t.inkSoft, fontSize: 13 },
axisLine: { lineStyle: { color: t.inkSoft } },
axisTick: { lineStyle: { color: t.inkSoft } },
splitLine: { lineStyle: { color: t.grid } },
},
yAxis: {
type: "value",
name: "Standard Error",
nameLocation: "center",
nameGap: 60,
nameTextStyle: { color: t.inkSoft, fontSize: 14 },
inverse: true,
min: 0,
max: 0.55,
axisLabel: {
color: t.inkSoft,
fontSize: 13,
formatter: val => val.toFixed(2),
},
axisLine: { lineStyle: { color: t.inkSoft } },
axisTick: { lineStyle: { color: t.inkSoft } },
splitLine: { lineStyle: { color: t.grid } },
},
series: [
{
name: "Studies",
type: "scatter",
data: studyData,
symbolSize: data => {
const w = 1 / (data[1] * data[1]);
return 8 + ((w - wMin) / (wMax - wMin)) * 16;
},
itemStyle: {
color: t.palette[0],
opacity: 0.85,
borderColor: t.pageBg,
borderWidth: 1.5,
},
markLine: {
silent: true,
symbol: ["none", "none"],
label: { show: false },
data: [
// Null effect reference (LOR = 0)
[
{ coord: [0, 0], lineStyle: { color: t.inkSoft, type: "dashed", width: 1.5 } },
{ coord: [0, maxSE] },
],
// Summary effect (LOR = −0.43)
[
{ coord: [summaryEffect, 0], lineStyle: { color: t.ink, type: "solid", width: 2.5 } },
{ coord: [summaryEffect, maxSE] },
],
// Left funnel boundary (pseudo 95% CI)
[
{ coord: [summaryEffect, 0], lineStyle: { color: t.palette[2], type: "dashed", width: 2, opacity: 0.8 } },
{ coord: [boundLeft, maxSE] },
],
// Right funnel boundary (pseudo 95% CI)
[
{ coord: [summaryEffect, 0], lineStyle: { color: t.palette[2], type: "dashed", width: 2, opacity: 0.8 } },
{ coord: [boundRight, maxSE] },
],
],
},
},
// Dummy series used only for legend icons
{
name: "Summary effect (−0.43)",
type: "line",
data: [],
lineStyle: { color: t.ink, type: "solid", width: 2.5 },
symbolSize: 0,
legendHoverLink: false,
},
{
name: "95% CI bounds",
type: "line",
data: [],
lineStyle: { color: t.palette[2], type: "dashed", width: 2 },
symbolSize: 0,
legendHoverLink: false,
},
{
name: "Null effect (0)",
type: "line",
data: [],
lineStyle: { color: t.inkSoft, type: "dashed", width: 1.5 },
symbolSize: 0,
legendHoverLink: false,
},
],
});
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/funnel-meta-analysis/echarts/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": "echarts",
"page": "https://anyplot.ai/funnel-meta-analysis/javascript/echarts",
"hub": "https://anyplot.ai/funnel-meta-analysis",
"code_json": "https://api.anyplot.ai/specs/funnel-meta-analysis/echarts/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/echarts/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/echarts/plot-dark.png",
"interactive_light_html": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/echarts/plot-light.html",
"interactive_dark_html": "https://storage.googleapis.com/anyplot-images/plots/funnel-meta-analysis/javascript/echarts/plot-dark.html",
"quality_score": 90.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Meta-Analysis Funnel Plot for Publication Bias on anyplot.ai.