Best article of the week? No: best article of the month.

If you have ten minutes to spare, please head over to The Economist and read their article entitled “Unreliable research: Trouble at the lab”.

Here’s an excerpt:

“In 2005 John Ioannidis, an epidemiologist from Stanford University, caused a stir with a paper showing why, as a matter of statistical logic, the idea that only one such paper in 20 gives a false-positive result was hugely optimistic. Instead, he argued, “most published research findings are probably false.” As he told the quadrennial International Congress on Peer Review and Biomedical Publication, held this September in Chicago, the problem has not gone away.

“Dr Ioannidis draws his stark conclusion on the basis that the customary approach to statistical significance ignores three things: the “statistical power” of the study (a measure of its ability to avoid type II errors, false negatives in which a real signal is missed in the noise); the unlikeliness of the hypothesis being tested; and the pervasive bias favouring the publication of claims to have found something new.”

Scientists and skeptics in general tend to turn a blind eye to the failings of science. As the old argument goes, “Science corrects itself”. True, it does, but in the meantime, what damage does it do when it is being poorly executed?

Drop whatever you are doing (including the baby! Drop that baby now!) and go read the article now!

Thanks to Mary Lim for bringing this to my attention. Dr. Ioannidis, who is briefly mentioned in the article, will be in Montreal at the end of the month for the Lorne Trottier Public Science Symposium.

And, for the record, I’m a big fan of Science. Love makes me very critical.