Why most published research findings are false: Ioannidis JP, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
By J. Brooks. 2008
745 citations recorded by the source corpus.
Subfields: Statistics and Probability, Medical & Health AI
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- John P. A. Ioannidis
- Haolun Shi
- Guosheng Yin
- Thomas A. Trikalinos
- Ari Holtzman
- Alex Wang
- Samuel R. Bowman
- Julian Michael
In Medical & Health AI
Citations in the corpus
- What Do NLP Researchers Believe? Results of the NLP Community Metasurvey (2022, background): “On the other hand, it could simply mean that many reported findings are of little importance or are not robust, which would arguably not make NLP unique among sciences (Ioannidis, 2005).”
- Charting the future of social psychology on stormy seas: Winners, losers, and recommendations (2016, background): “Stroebe (2016–in this issue) finds it necessary to defend social psychology against the sweeping claim by Ioannidis (1997) that most published research findings are false.”
- Reflections on the replication corner: In praise of conceptual replications (2015, neutral): “…that not only did Maniadis et al. successfully replicate Ariely et al. (2003): ironically, much of their paper presented a theoretical model of replications that was an exact replication of the model presented by Ioannidis (2005) in his widely cited “Why Most Published Research Findings are False.””
- An exploratory test for an excess of significant findings (2007, background): “However, undue emphasis on significance levels may bias the accumulated scientific evidence [5].”
- Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests (2018, background): “As there is a widespread notion that medical research is interpreted mainly based on p-value, Ioannidis (2005) claimed that most of the published findings in medicine are false.”