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Pretty much every time someone complains about the whole correlation != causation thing, it's a huge red flag that they didn't read the actual research or have

Pretty much every time someone complains about the whole correlation != causation thing, it's a huge red flag that they didn't read the actual research or have no experience in academic research. It's easily accounted for and is the lowest hanging methodological fruit, and pretty much is always addressed when actually appropriate. It's an undergrad stats thing, and I know for my degree I had to have at least a year of graduate level stats, and the same for undergrad.

toasterlovin 9y ago
On the other hand, epidemiology is fundamentally incapable of proving positive causation. It can prove that something is not a cause by showing that there is no correlation, but that’s it.
tomp 9y ago
the kind of conclusion as "all of 70% decrease was caused by this single factor" (as the title implies) is incredibly intelectually dishonest to ever make. So I'm not looking at the data from the perspective "I bet they were too stupid/uneducated to think about correlation != causation", but rather from the "looks like they're trying to find data to substantiate their political agenda" perspective. Edit: having said that, yeah, I don't have any actual research experience, and the data does look pretty convincing - as in, banning pesticides probably does contribute to a reduction in suicides a non-trivial amount.
- achileas 9y ago
  You're not looking at the data at all, and making assumptions about the scientists who did the research without even bothering to read beyond a podcast headline.
Chathamization 9y ago
It's an interesting reaction. "I didn't bother looking at the studies, but I bet the doctors who studied this didn't realize that correlation != causation, didn't realize that Sri Lanka had a civil war, didn't realize Sri Lanka's economy was growing, etc." It's worth keeping in mind when people wonder how there could be so many people who reject certain scientific findings. A lot of the time it's a similar attitude - "I'm not going to bother looking at the studies, but I'm guessing the people who studied it didn't think of the problem that immediately cam to my mind, and as such their results are probably wrong."
- achileas 9y ago
  I've always wondered if it was a defense mechanism of some people with certain attitudes about their own intelligence or achievement.
- tinymollusk 9y ago
  Outside of the slightly distasteful attitude ("I didn't bother" and "I bet" are slightly abrasive sounding), isn't the attitude one of the skeptic? It jibes with my understanding of how to make better decisions: don't start with the assumption something is true, question information before you store it in your brain. Annie Duke talks about this in her latest book.
  - achileas 9y ago
    No, that is being contrarian for its own sake. OP specifically said that they don't bother to look at or understand the actual research - that's not what a skeptic does.
    - tinymollusk 9y ago
      I suppose I believe it's less important whether or not we collectively determine the correctness of the other person, and more important that I use their contrarianism to question my own knowledge. I'm less interested in judging their argument and more interested in using their comments to evaluate my own. Kind of a "less wrong" approach, but focused on my own model of reality.
pseudonom- 9y ago
Whoa, that seems like a very strong claim claim and is contrary to my understanding. I know that instrumental variables can be a powerful approach, but it's not always easy to find a good instrument. And you can try to control for confounders, but it's hard to convince yourself you've gotten all of them. See, for example, https://arxiv.org/abs/1706.04692 https://arxiv.org/abs/1706.04692 where standard controls were of limited efficacy and it's only when they include an additional 3,700 controls that things start looking up. Then there are things like https://en.wikipedia.org/wiki/Parameter_identification_problem https://en.wikipedia.org/wiki/Parameter_identification_probl... and whole books like https://en.wikipedia.org/wiki/Causality_(book) https://en.wikipedia.org/wiki/Causality_(book) examining the problem and its' difficulty. Can you explain what you mean?
- achileas 9y ago
  Easily accounted for doesn't mean just proving absolute causality - you can account for the issue by either certain statistical tests giving evidence for causation, but more easily you write about associations, what gives you evidence for the reduction of confounds (strengthening your evidence, as they did in this paper), and, of course, papers are written to an audience that understands correlation != causation, and are written as such. People pointing out such an obvious thing that is always accounted for in various ways in research shows their ignorance of the specific article as well as the philosophy of science in general. It's just a reflexive response for some people at this point.

toasterlovin 9y ago

On the other hand, epidemiology is fundamentally incapable of proving positive causation. It can prove that something is not a cause by showing that there is no correlation, but that’s it.

tomp 9y ago

the kind of conclusion as "all of 70% decrease was caused by this single factor" (as the title implies) is incredibly intelectually dishonest to ever make. So I'm not looking at the data from the perspective "I bet they were too stupid/uneducated to think about correlation != causation", but rather from the "looks like they're trying to find data to substantiate their political agenda" perspective. Edit: having said that, yeah, I don't have any actual research experience, and the data does look pretty convincing - as in, banning pesticides probably does contribute to a reduction in suicides a non-trivial amount.

achileas 9y ago
You're not looking at the data at all, and making assumptions about the scientists who did the research without even bothering to read beyond a podcast headline.

Chathamization 9y ago

It's an interesting reaction. "I didn't bother looking at the studies, but I bet the doctors who studied this didn't realize that correlation != causation, didn't realize that Sri Lanka had a civil war, didn't realize Sri Lanka's economy was growing, etc." It's worth keeping in mind when people wonder how there could be so many people who reject certain scientific findings. A lot of the time it's a similar attitude - "I'm not going to bother looking at the studies, but I'm guessing the people who studied it didn't think of the problem that immediately cam to my mind, and as such their results are probably wrong."

achileas 9y ago
I've always wondered if it was a defense mechanism of some people with certain attitudes about their own intelligence or achievement.
tinymollusk 9y ago
Outside of the slightly distasteful attitude ("I didn't bother" and "I bet" are slightly abrasive sounding), isn't the attitude one of the skeptic? It jibes with my understanding of how to make better decisions: don't start with the assumption something is true, question information before you store it in your brain. Annie Duke talks about this in her latest book.
- achileas 9y ago
  No, that is being contrarian for its own sake. OP specifically said that they don't bother to look at or understand the actual research - that's not what a skeptic does.
  - tinymollusk 9y ago
    I suppose I believe it's less important whether or not we collectively determine the correctness of the other person, and more important that I use their contrarianism to question my own knowledge. I'm less interested in judging their argument and more interested in using their comments to evaluate my own. Kind of a "less wrong" approach, but focused on my own model of reality.

pseudonom- 9y ago

Whoa, that seems like a very strong claim claim and is contrary to my understanding. I know that instrumental variables can be a powerful approach, but it's not always easy to find a good instrument. And you can try to control for confounders, but it's hard to convince yourself you've gotten all of them. See, for example, https://arxiv.org/abs/1706.04692 https://arxiv.org/abs/1706.04692 where standard controls were of limited efficacy and it's only when they include an additional 3,700 controls that things start looking up. Then there are things like https://en.wikipedia.org/wiki/Parameter_identification_problem https://en.wikipedia.org/wiki/Parameter_identification_probl... and whole books like https://en.wikipedia.org/wiki/Causality_(book) https://en.wikipedia.org/wiki/Causality_(book) examining the problem and its' difficulty. Can you explain what you mean?

achileas 9y ago
Easily accounted for doesn't mean just proving absolute causality - you can account for the issue by either certain statistical tests giving evidence for causation, but more easily you write about associations, what gives you evidence for the reduction of confounds (strengthening your evidence, as they did in this paper), and, of course, papers are written to an audience that understands correlation != causation, and are written as such. People pointing out such an obvious thing that is always accounted for in various ways in research shows their ignorance of the specific article as well as the philosophy of science in general. It's just a reflexive response for some people at this point.