Discover more from Overcoming Bias
A recent Wall Street Journal article:
Dr. Ioannidis said "A new claim about a research finding is more likely to be false than true." The hotter the field of research the more likely its published findings should be viewed skeptically, he determined. Take the discovery that the risk of disease may vary between men and women, depending on their genes. Studies have prominently reported such sex differences for hypertension, schizophrenia and multiple sclerosis, as well as lung cancer and heart attacks. In research published last month in the Journal of the American Medical Association, Dr. Ioannidis and his colleagues analyzed 432 published research claims concerning gender and genes. Upon closer scrutiny, almost none of them held up. Only one was replicated. …
His 2005 essay "Why Most Published Research Findings Are False" remains the most downloaded technical paper [at] the journal PLoS Medicine … Another PLoS Medicine article … demonstrated that the likelihood of a published research result being true increases when that finding has been repeatedly replicated in multiple studies. … Earlier this year, informatics expert Murat Cokol and his colleagues at Columbia University sorted through 9.4 million research papers at the U.S. National Library of Medicine published from 1950 through 2004 in 4,000 journals. By raw count, just 596 had been formally retracted, Dr. Cokol reported.
Is anyone still surprised to hear these things? Hat tip to Giancarlo Ibargaen.
False Findings, Unretracted
the reason "Why Most Published Research Findings Are False" is the most downloaded technical paper is same reason WHO magazine sells more copies when it has a photo of B. Spears drugged and semi naked on the cover than say a photo of a moth. It is sensational - nothing more.
it is the very system that is criticized in this 'blog' that generates new papers and meta-analysis that contradicts previous findings. that is the strength of the scientific process. it is possible to be closer to an 'objective truth' without actually ever getting there.
Aristotle's thoughts on the motion of objects were better than nothing at explaining the world, which were superceded with Newton's and then by Einstein's. It is certain that all three models are 'wrong' - that hardly reduces the merit of them.
The famous quote "If I have seen further it is by standing on the shoulders of giants." should really read "If I have seen further it is by standing on the corpses of incorrect theories."
There is actually a very standard question in Statistics, generally refered to as the Law of Very Large Numbers: given a finite database, you can try to infer enough ideas so that a pointless one get out and is relevant -- that is basically the same idea.
The usual solution is to only make sensible assumption: easier to say in reasonable science with little history then Medical Science with Centuries of Documented Research and Billions at stake. The only other alternative is to actually reproduce the experiment, not claim it is well-documented enough to. Some scientist do not quote a result unless it was reproduced -- I recommend this information be linked to papers.
If retraction is too harsh a step for a minority opinion, then let's add a tag to it: the good news is that it would attract attention to things that might be hidden behind overlooked experimental designs, or assumptions. It would also help measure the actual ratio of false positive -- the 1:20 mentioned earlier is only the most common limit, not the actual rate. A lower limit would not make sense: it has more to do with the accuracy of measurements then the science behind.