An investigation of the false discovery rate and the misinterpretation of p-values

• Main Author: David Colquhoun
• Format: Article
• Language: English
• Published: The Royal Society 2014-01-01
• Series: Royal Society Open Science
• Subjects: significance tests; reproducibility; statistics; false discovery rate
• Online Access: https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.140216

If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations of t-tests. These mimic what is done in real life, which makes the results more persuasive. The simulation method is used also to evaluate the extent to which effect sizes are over-estimated, especially in underpowered experiments. A script is supplied to allow the reader to do simulations themselves, with numbers appropriate for their own work. It is concluded that if you wish to keep your false discovery rate below 5%, you need to use a three-sigma rule, or to insist on p≤0.001. And never use the word ‘significant’.