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Nancy Benedict's avatar

My primary question here, and I am a nurse with limited knowledge, is why strong anecdotal evidence cannot be used to make emergency medical decisions. This data compilation on IVM used in care homes in France came out in March of 2020. Residents being treated for scabies with IVM had an astonishingly low rate of Covid infections. If an EUA can be given for an experimental injection, why not for a long-tested and extraordinarily safe drug like IVM? This seems like sensible medicine to me.

https://www.clinmedjournals.org/articles/jide/journal-of-infectious-diseases-and-epidemiology-jide-7-202.php?jid=jide

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Richard Feinman's avatar

Here's my take on the problem:

A post on my substack noted that "The Introduction to a good statistics text will tell you that 'what we do in statistics is to put a number on our intuition.' .... The idea is that you start from the science, from the question to be answered and what the outcome will look like. You propose or apply a mathematical model to the results of your experiment. In other words, the medical or scientific question comes first.... A major defect in the medical literature is that often the opposite is what’s going on — many papers are trying to come up with an intuition to fit a number, trying to derive the science from the statistics. ....The implication, in these cases, is that your experiment did not have independent justification and the significance was revealed by the statistics. The corollary is that the type of experiment becomes more important than its quality."

The description of the case here: “A treatment to reduce stroke is tested in a clinical trial. In the treatment group, 2.3% of patients had a stroke vs 2.9% in the control arm. The question that everyone wants to know …” should be, first, the researchers assessment of how meaningful the procedure is relative to the data. Frank Harrell's comment pointing to Bayes may be helpful but it is the (philosophical) idea contained in Bayes that is key: statistics is taken as the belief in the data. Science is expected to be an intellectual activity. We trust that the researcher has enough training to interpret the experiment. Otherwise, who would have hired him? The most distressing thing about the advent of AI is that we ourselves have become like AI.

“For this, we look to the 95% confidence intervals.…” This is wrong. The key phrase in the post is "A treatment..." emphasis on "A." We might look first to our understanding, that is, our belief (a priori in Bayes terms).

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