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Posts Tagged Bayesian analysis

Beware The P-Value

Part of the mission of SBM is to continually prod discussion and examination of the relationship between science and medicine, with special attention on those beliefs and movements within medicine that we feel run counter to science and good medical practice. Chief among them is so-called complementary and alternative medicine (CAM) – although proponents are constantly tweaking the branding, for convenience I will simply refer to it as CAM.

Within academia I have found that CAM is promoted largely below the radar, with the deliberate absence of public debate and discussion. I have been told this directly, and that the reason is to avoid controversy. This stance assumes that CAM is a good thing and that any controversy would be unjustified, perhaps the result of bigotry rather than reason. It’s sad to see how successful this campaign has been, even among my fellow academics and scientists who should know better.

The reality is that CAM is fatally flawed in both philosophy and practice, and the claims of CAM proponents wither under direct light. I take some small solace in the observation that CAM is starting to be the victim of its own success – growing awareness of CAM is shedding some inevitable light on what it actually is. Further, because CAM proponents are constantly trying to bend and even break the rules of science, this forces a close examination of what those rules should actually be, how they work, and their strengths and weaknesses.

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Prior Probability: The Dirty Little Secret of “Evidence-Based Alternative Medicine”

This is actually the second entry in this series;† the first was Part V of the Homeopathy and Evidence-Based Medicine series, which began the discussion of why Evidence-Based Medicine (EBM) is not up to the task of evaluating highly implausible claims. That discussion made the point that EBM favors equivocal clinical trial data over basic science, even if the latter is both firmly established and refutes the clinical claim. It suggested that this failure in calculus is not an indictment of EBM’s originators, but rather was an understandable lapse on their part: it never occurred to them, even as recently as 1990, that EBM would soon be asked to judge contests pitting low powered, bias-prone clinical investigations and reviews against facts of nature elucidated by voluminous and rigorous experimentation. Thus although EBM correctly recognizes that basic science is an insufficient basis for determining the safety and effectiveness of a new medical treatment, it overlooks its necessary place in that exercise.

This entry develops the argument in a more formal way. In so doing it advocates a solution to the problem that has been offered by several others, but so far without real success: the adoption of Bayesian inference for evaluating clinical trial data.
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