tag:blogger.com,1999:blog-1812431336777691886.post8096505996814746043..comments2024-02-29T03:57:00.088-05:00Comments on The Mermaid's Tale: Who's at risk and why?Anne Buchananhttp://www.blogger.com/profile/09212151396672651221noreply@blogger.comBlogger2125tag:blogger.com,1999:blog-1812431336777691886.post-88848042824198575632011-09-03T09:59:50.585-04:002011-09-03T09:59:50.585-04:00I agree, causality very often _isn't_ simple, ...I agree, causality very often _isn't_ simple, obvious, or commonsensical. And yet people, from those whose aim it is to determine cause -- of anything, from disease to the London riots or the 9/11 attacks -- to those whose aim it is to interpret what it means to them (will I get cancer/heart disease/dementia?) often prefer to treat it as simple and obvious. This is good for companies selling, say, genetic risk estimates but bad for science and understanding.<br /><br />It's interesting about that 30% risk. Using a number of heart attack risk estimators online, I tried hard to kick my risk up higher, giving myself extreme values for cholesterol or weight, e.g., but I couldn't get it much higher. And, as you say, 30% is actually pretty low. But, most people would consider a 60 year old male smoker, weighing 400 pounds, with a total cholesterol of 300 to be at very high risk. And in fact _some_ people with that profile are in fact at 100% risk. Who? 30% of the people? Why isn't everyone?Anne Buchananhttps://www.blogger.com/profile/09212151396672651221noreply@blogger.comtag:blogger.com,1999:blog-1812431336777691886.post-30833097747331936162011-09-03T01:00:12.209-04:002011-09-03T01:00:12.209-04:00As the philosopher Judea Pearl has made clear, cau...As the philosopher Judea Pearl has made clear, causality isn't simple, obvious, or commonsensical. And, as a linguistic term, is often used in incommensurate ways. It *CAN* be defined, as Pearl does in his opus, Causality, but that definition does not apparently coincide with what many (most?) apparently mean when they use the term (if they mean anything coherent at all), including many (most?) scientists. Pearl attributes that incoherence to the users of the term, not the concept itself. And, he may well be right in that.<br /><br />I think Anne's points here reflect that confusion quite clearly. First, risk has nothing directly to do with causation (even in Pearl's sense): it refers merely to observed correlation between category membership and outcome with unknown causal structure. So, what does a 30% risk mean? It means a low correlation between the "risk factors" and the outcome. That's all. It is often taken to mean something causal, but without any real justification. I suspect most people, especially in medicine, treat these risk percentages as *propensities*: All those with the 30% "at risk" category membership have a greater propensity for the outcome than those with, say, a 10% "at risk" category. <br /><br />The reasoning is something like this: imagine two coins: one has a .5 probability of coming up heads and the other a .8 probability. The second has a greater propensity for heads, or so it seems. The problem is that the imagining here is artificial. We can easily construct a physical model of a .5 coin (or, al least something close to it), but a .8 coin is not so easy: we now hove to posit specific *causal* forces to produce the .8 that were not seemingly needed in the simple 50/50 coin. So, they don't just differ in propensity (if at all), but rather in causal structure. Or so it seems...John R. Vokeyhttps://www.blogger.com/profile/03822243132435056442noreply@blogger.com