Carlisle’s statistics bombshell names and shames rigged clinical trials by Leonid Schneider.
From the post:
John Carlisle is a British anaesthesiologist, who works in a seaside Torbay Hospital near Exeter, at the English Channel. Despite not being a professor or in academia at all, he is a legend in medical research, because his amazing statistics skills and his fearlessness to use them exposed scientific fraud of several of his esteemed anaesthesiologist colleagues and professors: the retraction record holder Yoshitaka Fujii and his partner Yuhji Saitoh, as well as Scott Reuben and Joachim Boldt. This method needs no access to the original data: the number presented in the published paper suffice to check if they are actually real. Carlisle was fortunate also to have the support of his journal, Anaesthesia, when evidence of data manipulations in their clinical trials was found using his methodology. Now, the editor Carlisle dropped a major bomb by exposing many likely rigged clinical trial publications not only in his own Anaesthesia, but in five more anaesthesiology journals and two “general” ones, the stellar medical research outlets NEJM and JAMA. The clinical trials exposed in the latter for their unrealistic statistics are therefore from various fields of medicine, not just anaesthesiology. The medical publishing scandal caused by Carlisle now is perfect, and the elite journals had no choice but to announce investigations which they even intend to coordinate. Time will show how seriously their effort is meant.
Carlisle’s bombshell paper “Data fabrication and other reasons for non-random sampling in 5087 randomised, controlled trials in anaesthetic and general medical journals” was published today in Anaesthesia, Carlisle 2017, DOI: 10.1111/anae.13962. It is accompanied by an explanatory editorial, Loadsman & McCulloch 2017, doi: 10.1111/anae.13938. A Guardian article written by Stephen Buranyi provides the details. There is also another, earlier editorial in Anaesthesia, which explains Carlisle’s methodology rather well (Pandit, 2012).
… (emphasis in original)
Cutting to the chase, Carlisle found 90 papers with statistical patterns unlikely to occur by chance in 5,087 clinical trials.
There is a wealth of science papers to be investigated, Sarah Boon, in 21st Century Science Overload points out (2016) there are 2.5 million new scientific papers published every year, in 28,100 active scholarly peer-reviewed journals (2014).
Since Carlisle has done eight (8) journals, that leaves ~28,092 for your review. 😉
Happy hunting!
PS: I can easily imagine an exercise along these lines being the final project for a data mining curriculum. You?