tag:blogger.com,1999:blog-4683970826895755480.post9165011472637499592..comments2024-03-28T21:32:26.550+00:00Comments on Bruce Charlton's Notions: My alpha MSH RIA study - The biggest waste of time of my life?...Bruce Charltonhttp://www.blogger.com/profile/09615189090601688535noreply@blogger.comBlogger4125tag:blogger.com,1999:blog-4683970826895755480.post-43571832409880058512010-10-24T10:25:46.230+01:002010-10-24T10:25:46.230+01:00Yes - The Atlantic piece is semi-correct; it gets ...Yes - The Atlantic piece is semi-correct; it gets the diagnosis right, but for the wrong reason, based on faulty understanding - so the prescription is likely to be dangerous. <br /><br />Medical research has been roughly doubling in size every decade for a long time. <br /><br />Naturally therefore (to look no further for causes), by now medical research is almost all rubbish so it is perfectly rational to operate on the basis that it is *all* rubbish - unless specifically proven otherwise by clear, commonsensical criteria (preferably confirmed by personal experience).Bruce Charltonhttps://www.blogger.com/profile/09615189090601688535noreply@blogger.comtag:blogger.com,1999:blog-4683970826895755480.post-18038189589122607132010-10-24T09:31:42.410+01:002010-10-24T09:31:42.410+01:00Excellent. Meantime I have stumbled across this
...Excellent. Meantime I have stumbled across this <br />http://www.theatlantic.com/magazine/archive/2010/11/lies-damned-lies-and-medical-science/8269/2/<br /><br />It seems to be a verbose version of my own dictum:<br /><br />"All medical research is rubbish" is a better approximation to the truth than almost all medical research.deariemenoreply@blogger.comtag:blogger.com,1999:blog-4683970826895755480.post-64105885615515419662010-10-24T08:14:02.176+01:002010-10-24T08:14:02.176+01:00In asking that question you have answered it.
I ...In asking that question you have answered it. <br /><br />I was a professional academic epidemiologist and public health physician for three years and saw for myself the indifference to the actual validity of measurements upon which everything is based. <br /><br />There is an intrinsic but unspoken assumption that volume of data can compensate for poor quality of data - this runs through the social sciences. <br /><br />This misunderstanding seems to arise from a confusion of random noise with systematic bias. <br /><br />I allude to this here: http://www.trialsjournal.com/content/2/1/2 <br /><br />But I now realize that my main writing on the subject (The scope and nature of epidemiology) is not available online without subscription - so I will post it onto this blog later today.Bruce Charltonhttps://www.blogger.com/profile/09615189090601688535noreply@blogger.comtag:blogger.com,1999:blog-4683970826895755480.post-81084516127096108712010-10-24T00:32:38.281+01:002010-10-24T00:32:38.281+01:00Much of science does boil down to questions of how...Much of science does boil down to questions of how measurements, or measurement-substitutes, are made. I was pondering the "epidemic" of Type 2 Diabetes recently. There's lots of epidemiology, but it occurred to me that the discussions that the layman like me sees don't touch on measurement - in this context, that would mean that they don't answer the question "how stable is the diagnosis of diabetes?". Is it diagnosed by some measurement exceeding a threshold? Has the threshold been held constant over time? Has the mode of measurement been held constant? Are the diagnoses subject to medical fashion, or to financial incentives offered to doctors?<br /><br />(P.S. Someone opined that the "epidemic" was as important as Global Warming. I hope that I managed to suppress my snort.)deariemenoreply@blogger.com