Why Most Published Research Findings Are False by John Ioannidis
Argues that a large proportion of reported scientific findings are likely false positives, driven by low statistical power, multiple testing, flexible analytic choices, selective reporting, and biases reinforced by publication incentives. Using a Bayesian framework, it explains how low prior probabilities, limited power, and bias reduce the positive predictive value of claimed effects. It calls for reforms such as larger, better-designed studies, preregistration, transparency, and replication to make research more reliable.
- Published
- 2005
- Nationality
- Unknown
- Length
- Very Short
- Pages
- 6-8
- Original Language
- English
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- Alternate Titles
- None
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