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This would be like saying that millions died a few months before they normally would 30-40 years later because they had higher levels of stress due to the accid

by ein0p 2y ago

This would be like saying that millions died a few months before they normally would 30-40 years later because they had higher levels of stress due to the accident. The statistical (let alone causal!) connection in such things is so tenuous, it’s utterly meaningless. Control groups or randomized testing is impossible even in principle. Meanwhile, we can’t even reliably determine if eating eggs increases cholesterol.

FrustratedMonky 2y ago
"saying that millions died a few months before they normally would 30-40 years later because they had higher levels of stress due to the accident." Isn't this exactly the type of reasoning they are using? You seem to be using this as an example to refute the study, when that is exactly the point. I just think the whole "statistics is magic so we should not trust any science and go back to living in trees" trope is getting a bit tired. It is 21st century, because people have learned their statistics from the internet doesn't mean studies are invalid. The whole point is that there are methods to determine if something is " utterly meaningless" beyond a knee jerk reaction.
- hackeraccount 2y ago
  As long as you can accept that kind of statistical argument for things that you did not agree with a priori.
  - FrustratedMonky 2y ago
    Well. They didn't consult with me on this study to see if I agreed a priori. But I am able to understand what they are attempting to quantify. I'm just not in the camp of something being difficult means it is garbage. It isn't that hard to conceptualize: -> traumatic event happens, -> there are follow on ramifications, -> some of them shorten life spans. -> And a shortened life span means death. As others in the thread said. Maybe something like " Quality-adjust life years (QALYs)" would have been more generalizable metric.
    - hackeraccount 2y ago
      I understand the logic it just seems like using that chain of consequences seems to produce weird results i.e. Item A kills 1% of the population a year, item B kill 1% a year, Item C kills 1% a year but somehow only 1% of the population dies every year. Though QALYs may get at that.
      - FrustratedMonky 2y ago
        Ok. So kind of like problem with Drake Equation. Depending on made up % for each variable, can have wild swings. I don't think that is the case here. The 'science' around counting deaths is older and more fleshed out than you are giving credit. People have been studying the impact of different types of events and co-factors on counting deaths for many decades. This isn't just winging it with some new made up statistics.

by ein0p 2y ago

FrustratedMonky 2y ago

"saying that millions died a few months before they normally would 30-40 years later because they had higher levels of stress due to the accident." Isn't this exactly the type of reasoning they are using? You seem to be using this as an example to refute the study, when that is exactly the point. I just think the whole "statistics is magic so we should not trust any science and go back to living in trees" trope is getting a bit tired. It is 21st century, because people have learned their statistics from the internet doesn't mean studies are invalid. The whole point is that there are methods to determine if something is " utterly meaningless" beyond a knee jerk reaction.

hackeraccount 2y ago
As long as you can accept that kind of statistical argument for things that you did not agree with a priori.
- FrustratedMonky 2y ago
  Well. They didn't consult with me on this study to see if I agreed a priori. But I am able to understand what they are attempting to quantify. I'm just not in the camp of something being difficult means it is garbage. It isn't that hard to conceptualize: -> traumatic event happens, -> there are follow on ramifications, -> some of them shorten life spans. -> And a shortened life span means death. As others in the thread said. Maybe something like " Quality-adjust life years (QALYs)" would have been more generalizable metric.
  - hackeraccount 2y ago
    I understand the logic it just seems like using that chain of consequences seems to produce weird results i.e. Item A kills 1% of the population a year, item B kill 1% a year, Item C kills 1% a year but somehow only 1% of the population dies every year. Though QALYs may get at that.
    - FrustratedMonky 2y ago
      Ok. So kind of like problem with Drake Equation. Depending on made up % for each variable, can have wild swings. I don't think that is the case here. The 'science' around counting deaths is older and more fleshed out than you are giving credit. People have been studying the impact of different types of events and co-factors on counting deaths for many decades. This isn't just winging it with some new made up statistics.