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Richard Horton writes that a recent symposium on the reproducibility and reliability of biomedical research discussed one of the most sensitive issues in science today: the idea that something has gone fundamentally wrong with science (PDF), one of our greatest human creations. The case against science is straightforward: much of the scientific literature, perhaps half, may simply be untrue. Afflicted by studies with small sample sizes, tiny effects, invalid exploratory analyses, and flagrant conflicts of interest, together with an obsession for pursuing fashionable trends of dubious importance, science has taken a turn towards darkness. According to Horton, editor-in-chief of The Lancet, a United Kingdom-based medical journal, the apparent endemicity of bad research behaviour is alarming. In their quest for telling a compelling story, scientists too often sculpt data to fit their preferred theory of the world or retrofit hypotheses to fit their data.
Can bad scientific practices be fixed? Part of the problem is that no-one is incentivized to be right. Instead, scientists are incentivized to be productive and innovative. Tony Weidberg says that the particle physics community now invests great effort into intensive checking and rechecking of data prior to publication following several high-profile errors,. By filtering results through independent working groups, physicists are encouraged to criticize. Good criticism is rewarded. The goal is a reliable result, and the incentives for scientists are aligned around this goal. "The good news is that science is beginning to take some of its worst failings very seriously," says Horton. "The bad news is that nobody is ready to take the first step to clean up the system."
[Editor's Comment: Original Submission]
(Score: 2) by FatPhil on Wednesday May 27 2015, @10:05AM
This is a good read:
"""
Bayesian Critique of Statistics in Health: The Great
Health Hoax
by Robert Matthews
The plain fact is that 70 years ago Ronald Fisher gave scientists
a mathematical machine for turning baloney into breakthroughs,
and flukes into funding. It is time to pull the plug.
"""
That was over a decade ago, and is written for those who already understand the problem. This one's far more explanatory:
An investigation of the false discovery rate and the misinterpretation of p-values -- David Colquhoun
DOI: 10.1098/rsos.140216 Published 19 November 2014
http://rsos.royalsocietypublishing.org/content/1/3/140216
It should be required reading for everyone going into academia, no matter which discipline. It's worth reading to the end, it never stops not pulling punches (even down to naming wrongdoers).
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 0) by Anonymous Coward on Wednesday May 27 2015, @02:40PM
Here are some more discussions of how p-values are (mis)used:
http://www.nature.com/news/scientific-method-statistical-errors-1.14700 [nature.com]
http://www.nature.com/news/statistics-p-values-are-just-the-tip-of-the-iceberg-1.17412 [nature.com]