A rule of thumb among biotechnology venture-capitalists is that half of published research cannot be replicated. Even that may be optimistic. Last year researchers at one biotech firm, Amgen, found they could reproduce just six of 53 “landmark” studies in cancer research. - Mitchell Tsai

Earlier, a group at Bayer, a drug company, managed to repeat just a quarter of 67 similarly important papers. A leading computer scientist frets that three-quarters of papers in his subfield are bunk. - Mitchell Tsai

In 2000-10 roughly 80,000 patients took part in clinical trials based on research that was later retracted because of mistakes or improprieties. - Mitchell Tsai

One reason is the competitiveness of science. In the 1950s, when modern academic research took shape after its successes in the second world war, it was still a rarefied pastime. The entire club of scientists numbered a few hundred thousand.As their ranks have swelled, to 6m-7m active researchers on the latest reckoning, scientists have lost their taste for self-policing and quality control. The obligation to “publish or perish” has come to rule over academic life. Competition for jobs is cut-throat. - Mitchell Tsai

In April, for instance, a paper in PLoS ONE, a journal, reported that nine separate experiments had not managed to reproduce the results of a famous study from 1998 purporting to show that thinking about a professor before taking an intelligence test leads to a higher score than imagining a football hooligan. http://www.economist.com/news... - Mitchell Tsai

Statistical mistakes are widespread. The peer reviewers who evaluate papers before journals commit to publishing them are much worse at spotting mistakes than they or others appreciate. Professional pressure, competition and ambition push scientists to publish more quickly than would be wise. A career structure which lays great stress on publishing copious papers exacerbates all these problems. “There is no cost to getting things wrong,” says Brian Nosek, a psychologist at the University of Virginia who has taken an interest in his discipline’s persistent errors. “The cost is not getting them published.” - Mitchell Tsai

A study in April by Dr Ioannidis and colleagues found that in neuroscience the typical statistical power is a dismal 0.21; writing in Perspectives on Psychological Science, Marjan Bakker of the University of Amsterdam and colleagues reckon that in that field the average power is 0.35. - Mitchell Tsai

Consider 1,000 hypotheses being tested of which just 100 are true. Studies with a power of 0.8 will find 80 of them, missing 20 because of false negatives. Of the 900 hypotheses that are wrong, 5%—that is, 45 of them—will look right because of type I errors. Add the false positives to the 80 true positives and you have 125 positive results, fully a third of which are specious. - Mitchell Tsai

If you dropped the statistical power from 0.8 to 0.4, which would seem realistic for many fields, you would still have 45 false positives but only 40 true positives. More than half your positive results would be wrong. - Mitchell Tsai