PLoS Med. 2005 Aug; 2(8): e124.
Published online 2005 Aug 30. doi: 10.1371/journal.pmed.0020124
PMCID: PMC1182327

Why Most Published Research Findings Are False

John P. A. Ioannidis
Author information â–º Copyright and License information â–º
See "Minimizing Mistakes and Embracing Uncertainty" , e272.
See "Truth, Probability, and Frameworks" in volume 2, e361.
See "Power, Reliability, and Heterogeneous Results" in volume 2, e386.
See "The Clinical Interpretation of Research" in volume 2, e395.
See "Author's Reply" in volume 2, e398.
See "Why Most Published Research Findings Are False: Problems in the Analysis" in volume 4, e168.
See "Why Most Published Research Findings Are False: Author's Reply to Goodman and Greenland" in volume 4, e215.
See "Why Current Publication Practices May Distort Science" in volume 5, e201. This article has been cited by other articles in PMC.

Abstract
Summary

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true
to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number
and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a
scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may
often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

Published research findings are sometimes refuted by subsequent evidence, with ensuing confusion and disappointment. Refutation and controversy is seen across the range of research designs, from clinical trials and traditional epidemiological studies [1â€
“3] to the most modern molecular research [4,5]. There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims [6–8]. However, this should not be surprising. It can be
proven that most claimed research findings are false. Here I will examine the key factors that influence this problem and some corollaries thereof.


Modeling the Framework for False Positive Findings




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