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Publication Bias Simulator

Watch how file-drawer bias distorts a scientific literature: run many independent studies with a small true anomaly rate, publish only the statistically significant ones, and see the visible published rate pull away from the true rate as unpublished null results pile up.

Society & Economics2DEasy60 FPS📱 Mobile-adapted⇄ 3D version

This simulator streams a large population of independent scientific studies, each testing whether something anomalous is really there. A small, adjustable fraction genuinely are — the rest are pure noise, and statistical testing guarantees that a fixed share of noise studies will still cross the significance threshold by chance alone. Toggle whether only "significant" results get published, and watch the visible literature's apparent anomaly rate pull away from the true underlying rate as the unpublished file drawer fills up — the same file-drawer and multiple-comparisons dynamic documented across real meta-science and cited to explain inflated positive-result rates in exploratory research.

⚙ Under the hood

Publication bias inflates the perceived rate of anomalies by only showing statistically significant results.

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2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install