Comment by jstummbillig
4 hours ago
The comment insinuates that the study did not control for age. The study controlled for age.
It's not terrible to not make a good point, but it's not a good point. The not good points should not be ranked highly.
4 hours ago
The comment insinuates that the study did not control for age. The study controlled for age.
It's not terrible to not make a good point, but it's not a good point. The not good points should not be ranked highly.
But after the study controls for age the starkness of the effect more or less disappears (eyeballing Fig 1, the 2nd graph).
It turns out that there is a profession with a lowest risk of getting Alzheimer's (duh, one had to exist) and it looks like a slight outlier (it's the lowest, we'd expect that one to look like a slight outlier). As outliers go it isn't that impressive, it looks like it is part of a fairly boring distribution. We just plotted 400 data points on the graph, the 1/400 chance weird data point is going to look a little weird. We're actually just reading a lot into the fact that the 2nd data point in ambulance drivers which isn't all that convincing.
Not to knock the study, I'm sure it is a great study. Lots of science done. They do good graphs and all that. But the study appears to be telling me that Alzheimer's is random with respect to occupation and ideally don't spend so much time on the road if you want to live to see old age.
It's getting hard to find any study posted without a kneejerk "correlation does not equal causation" take as if that's not something researchers have to control for in order to even conduct the study in the first place, let alone publish
The institutional media departments, journalists, and headline writers add back in the insinuated causation and effect size as a routine matter. That way we can't find fault with the researchers for their clickbait study.