4 ms·

The usual strategy is to control for smoking. If nuclear test rate correlates with lung cancer rate, but does not correlate with non-smoker lung cancer rate, nu

The usual strategy is to control for smoking. If nuclear test rate correlates with lung cancer rate, but does not correlate with non-smoker lung cancer rate, nuclear test is not causing lung cancer. Epidemiology is a field of study about how to do this right. One of the great achievement of humanity in the 20th century was advance of epidemiology.

nonbel 8y ago
>"The usual strategy is to control for smoking. If nuclear test rate correlates with lung cancer rate, but does not correlate with non-smoker lung cancer rate, nuclear test is not causing lung cancer." I'm not really concerned with whether there is, or is not, a correlation, I already know there is a correlation. I am concerned about: How much of the increase in lung cancer incidence we see in the data could be accounted for via exposure to radiation from nuclear tests? I doubt it is zero, but it could be relatively negligible I suppose. The timing of it does overlap quite well though.
- cbkeller 8y ago
  This is missing their point: you can distinguish the two potential causes by comparing lung cancer incidence rate through time for smokers versus non-smokers. If nuclear tests are a significant factor in lung cancer rate, we should still see a correlation between lung cancer incidence and nuclear test frequency when looking at people with no exposure to cigarette smoke. If the correlation in the general population just a coincidence, we should not.
  - nonbel 8y ago
    See here: https://news.ycombinator.com/item?id=18863438 https://news.ycombinator.com/item?id=18863438
nonbel 8y ago
But here you go: >"the lung cancer mortality rate has risen substantially between 1914 and 1968 among persons who never smoked cigarettes. For white males the relative increase for ages 35--84 years has been about 15-fold; the relative increase for ages 65--84 years has been about 30-fold." https://www.ncbi.nlm.nih.gov/pubmed/285289 https://www.ncbi.nlm.nih.gov/pubmed/285289
- cbkeller 8y ago
  That's interesting -- doesn't seem to have a graph, but states a significant increase between 1914 and 1967 in nonsmokers. There doesn't appear to be any control for secondhand smoke, however, which could also be a significant factor over that time period.
  - sanxiyn 8y ago
    My impression is that second-hand smoking is considered insufficient to explain epidemiology of non-smoker lung cancer; see my other comments.
  - nonbel 8y ago
    Sure, another thing to consider is fallout incorporated into tobacco and then smoked... But do you see why I didn't care if a correlation existed? There are a bunch of ways to explain such a correlation. That line of reasoning was based on the affirming the consequent fallacy[1]: If H: Nuclear tests are a significant factor in lung cancer rate Then O: We should still see a correlation between lung cancer incidence and nuclear test frequency [in non-smokers] We can't conclude "O is true, therefore H" (since there are a million potential reasons for O besides H), so we don't learn anything from it. Now if O had been some very specific prediction unlikely to arise from other hypotheses, I would care. In terms of Bayes' Rule, I only care if p( O|H[0] ) dominates all the other possibilities (H[1:n]) in the denominator. The mere existence of a positive correlation isn't specific enough for me to care: p( H[0]|O ) = p( H[0] )*p( O|H[0] )/sum( p( H[0:n] )*p( O|H[0:n] ) ) [1] https://en.wikipedia.org/wiki/Affirming_the_consequent https://en.wikipedia.org/wiki/Affirming_the_consequent
    - sanxiyn 8y ago
      Yes, epidemiology is not deductive, and in the end it depends on whether observation is "specific enough" for you st unlikely to arise from other hypotheses, which in turn depends on your prior, which is informed by laboratory results in addition to field results. Epidemiology is a truly fascinating subject.

nonbel 8y ago

>"The usual strategy is to control for smoking. If nuclear test rate correlates with lung cancer rate, but does not correlate with non-smoker lung cancer rate, nuclear test is not causing lung cancer." I'm not really concerned with whether there is, or is not, a correlation, I already know there is a correlation. I am concerned about: How much of the increase in lung cancer incidence we see in the data could be accounted for via exposure to radiation from nuclear tests? I doubt it is zero, but it could be relatively negligible I suppose. The timing of it does overlap quite well though.

cbkeller 8y ago
This is missing their point: you can distinguish the two potential causes by comparing lung cancer incidence rate through time for smokers versus non-smokers. If nuclear tests are a significant factor in lung cancer rate, we should still see a correlation between lung cancer incidence and nuclear test frequency when looking at people with no exposure to cigarette smoke. If the correlation in the general population just a coincidence, we should not.
- nonbel 8y ago
  See here: https://news.ycombinator.com/item?id=18863438 https://news.ycombinator.com/item?id=18863438

nonbel 8y ago

But here you go: >"the lung cancer mortality rate has risen substantially between 1914 and 1968 among persons who never smoked cigarettes. For white males the relative increase for ages 35--84 years has been about 15-fold; the relative increase for ages 65--84 years has been about 30-fold." https://www.ncbi.nlm.nih.gov/pubmed/285289 https://www.ncbi.nlm.nih.gov/pubmed/285289

cbkeller 8y ago
That's interesting -- doesn't seem to have a graph, but states a significant increase between 1914 and 1967 in nonsmokers. There doesn't appear to be any control for secondhand smoke, however, which could also be a significant factor over that time period.
- sanxiyn 8y ago
  My impression is that second-hand smoking is considered insufficient to explain epidemiology of non-smoker lung cancer; see my other comments.
- nonbel 8y ago
  Sure, another thing to consider is fallout incorporated into tobacco and then smoked... But do you see why I didn't care if a correlation existed? There are a bunch of ways to explain such a correlation. That line of reasoning was based on the affirming the consequent fallacy[1]: If H: Nuclear tests are a significant factor in lung cancer rate Then O: We should still see a correlation between lung cancer incidence and nuclear test frequency [in non-smokers] We can't conclude "O is true, therefore H" (since there are a million potential reasons for O besides H), so we don't learn anything from it. Now if O had been some very specific prediction unlikely to arise from other hypotheses, I would care. In terms of Bayes' Rule, I only care if p( O|H[0] ) dominates all the other possibilities (H[1:n]) in the denominator. The mere existence of a positive correlation isn't specific enough for me to care: p( H[0]|O ) = p( H[0] )*p( O|H[0] )/sum( p( H[0:n] )*p( O|H[0:n] ) ) [1] https://en.wikipedia.org/wiki/Affirming_the_consequent https://en.wikipedia.org/wiki/Affirming_the_consequent
  - sanxiyn 8y ago
    Yes, epidemiology is not deductive, and in the end it depends on whether observation is "specific enough" for you st unlikely to arise from other hypotheses, which in turn depends on your prior, which is informed by laboratory results in addition to field results. Epidemiology is a truly fascinating subject.