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# Publication bias and the funnel plot

- Bias

Studies with positive results get published more than negative ones; when the negatives are missing, the effect looks bigger.

Updated Nov 5, 2026

## Key points

- Positive results are published more, sooner and in more widely read journals; negative ones may never be published.
- Funnel: effect on the horizontal axis, precision on the vertical; large studies at the top and close together, small ones at the bottom and spread out.
- Asymmetry: small studies missing on the no-effect side; suggests publication bias, but has other causes (heterogeneity, poorer small studies, chance).
- With fewer than about 10 studies the funnel is unreliable.
- Prevention: prospective trial registration, searching for unpublished studies and registries, and publishing all results.

## What it is

Publication bias happens when whether a study is published depends on the direction or significance of its results. Small studies with no effect go unpublished, and a review that finds only what was published overestimates the benefit. The funnel plot places each study by its effect and its precision: without bias it forms a symmetrical funnel; if small studies are missing on one side, it is asymmetrical. It is one form of bias due to missing results, alongside selective outcome reporting.

## How it arises

- Authors and journals prefer significant, novel results.
- Small studies with null results are abandoned or published late.
- Within a published study, favourable outcomes are reported and others left out (selective reporting).

## Worked example

- Data (made up): 20 trials of a treatment were registered: 10 with a positive effect and 10 with no effect.
- 9 of the 10 positive trials were published (90 %) and 3 of the 10 null trials (30 %).
- Published: 9 + 3 = 12 trials; positive ones make up 9 / 12 = 75 %.
- In reality, positive trials were 10 / 20 = 50 %: the published literature exaggerates the favourable share.
- Probability of publication: 90 % / 30 % = 3 times higher for a positive result.
- In the funnel, the bottom corner on the no-effect side is empty: the small null trials are missing.
- Reading: a meta-analysis of published trials alone would overestimate the benefit; the review must search the registries.

## Markers

- Funnel
- Asymmetry
- Trial registry
- Selective reporting

## How to prevent or control it

- Register every trial before it starts, in public registries brought together by the WHO International Clinical Trials Registry Platform.
- Search trial registries, conference abstracts and grey literature during a systematic review.
- Compare the outcomes in the registered protocol with those published to detect selective reporting.

## Common pitfalls

- Blaming all funnel asymmetry on publication bias: heterogeneity, poorer small studies or chance also cause it.
- Interpreting a funnel with 5 studies: it lacks the power to show asymmetry.

## Memory aid

The drawer keeps the negatives: unless you open the drawer (the registries), the funnel stays lopsided.

## Test yourself

Think of the answer, then tap the question to see it.

## What is publication bias?

When whether a study is published depends on the direction or significance of its results, so the published evidence overestimates the effect.

## What does an asymmetrical funnel plot show?

That small studies are missing on one side (usually the no-effect side); it suggests publication bias, though other causes are possible.

## Which measure helps most to prevent publication bias?

Prospective registration of every trial in a public registry before the first patient is enrolled.

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## Connections

## Related 5

- [Systematic review](https://durgical.com/en/epidemiology/systematic-review/)
- [Meta-analysis](https://durgical.com/en/epidemiology/meta-analysis/)
- [The GRADE system](https://durgical.com/en/epidemiology/the-grade-system/)
- [Selection bias](https://durgical.com/en/epidemiology/selection-bias/)
- [Critical appraisal of a paper](https://durgical.com/en/epidemiology/critical-appraisal-of-a-paper/)

[← All of epidemiology](https://durgical.com/en/epidemiology/)

Educational content on epidemiological and statistical methods; the examples use made-up numbers to teach the calculation. Not a clinical or legal guide: current Colombian rules are in the official sources.

Sources: [Chapter 13: Assessing risk of bias due to missing evidence in a meta-analysis](https://www.cochrane.org/authors/handbooks-and-manuals/handbook/current/chapter-13) (Cochrane, 2026); [International Clinical Trials Registry Platform (ICTRP)](https://www.who.int/tools/clinical-trials-registry-platform) (World Health Organization, 2026).

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Representative model, for educational purposes only.

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Source: https://durgical.com/en/epidemiology/publication-bias-and-the-funnel-plot/
License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Cite as: DurgiPedia (durgical.com), https://durgical.com/en/epidemiology/publication-bias-and-the-funnel-plot/