What is Publication bias?
Publication bias is the systematic tendency for journals to publish studies with positive or significant results while rejecting studies with null or negative findings. This creates a distorted literature that overestimates effect sizes and inflates the apparent evidence base.
How it works
The ‘file drawer problem’ (Rosenthal, 1979) means that for every published positive study, there may be several unpublished null studies that were conducted but never reported. This makes meta-analyses unreliable: they analyze only the visible (published) portion of the evidence, not the full body of research. Publication bias also distorts researchers’ incentives, encouraging p-hacking and HARKing to produce publishable positive results. Registered reports (where journals accept papers based on methodology before results are known) are the primary remedy.
Applied example
A pharmaceutical company conducts ten trials of a new drug. Three show significant effects and are published in major journals. Seven show no effect and are filed away. Doctors prescribing the drug see a literature showing 100% positive results, when the true evidence base shows only 30% positive results.
Why it matters
Publication bias means the published literature is a systematically distorted sample of all research conducted, undermining evidence-based practice across medicine, psychology, and policy.
