5 ms·

Doesn't that only rule out the genetic factor? It doesn't establish causation of smoking -> tar -> cancer. Like you said, you have to assume smoking causes the

Doesn't that only rule out the genetic factor? It doesn't establish causation of smoking -> tar -> cancer. Like you said, you have to assume smoking causes the tar in addition to assuming that a correlation between tar and cancer indicates causation. I feel that directly controlling the causative factor is the only way to verify the chain of causation.

Geminidog 6y ago
Actually under your experiment both could be still be causative factors. Determining Tar correlates with cancer does not eliminate the genetic factor. The only assumption for direct control of the hypothesized causative factor that needs to be made is that your influence on the causative factor is 100% side effect free. This is not fully possible in reality but still assuming this in your experiments allows you to arrive at a conclusion without assuming other correlations.
DavidSJ 6y ago
We're comparing two competing hypotheses to explain the correlation between smoking and cancer. Like I said, we can always introduce new ad-hoc hypotheses, but good science isn't done willy nilly, it's done with background knowledge of how the systems might plausibly work. The two hypotheses are: (1) smoking → tar → cancer (2) smoking ← genes → cancer Note that (1) contains the sub-hypothesis (A) smoking → tar, which is also compatible with (2). The super-graph containing both graphs is: ————genes———— ↓ ↓ smoking → tar → cancer In that super-graph, there is only one possible explanation for a correlation between smoking and tar: smoking causing tar. So if we see that correlation, then barring alternative hypotheses, we know the causation smoking → tar is true. (Again, we could always hypothesize other causal explanations, but we're presuming no one has yet submitted a plausible alternative explanation.) Now once smoking → tar is established, we are still left with two possible explanations for the observed correlation between smoking and cancer: (1) smoking → tar → cancer (2+A) tar ← smoking ← genes → cancer This is where controlling for smoking behavior comes in. Once we do that, we've severed the indirect statistical link between tar and cancer in graph (2+A). Thus if a correlation still persists between tar and cancer after this statistical control, we've ruled out (2+A), leaving only (1).
- Geminidog 6y ago
  Right I understand we're introducing new hypothesis, but it still stands. By controlling the causative factor no new hypothesis can undermine an established causation assuming that there are no side effects when we trigger a causation event. Think about it. This means that causation is actually established versus the other method which is a flimsier verification. Another way to look at it is that rather then introducing a new "hypothesis" you had to introduce assumptions about causation. You're thinking in terms of math where you can control your primitives and set a domain and range. In science none of these can be fully controlled and a "new hypothesis" does indeed apply. Think about it. If I introduce a new hypothesis in the real world that actually lends good evidence in support of say the cancer outcome I cannot just discount it and say it's not good science. You can only restrict your universe like this in the world of math and logic, in the real world you have to except any reasonable evidence that comes your way. In practice however, most scientists make a bunch of assumptions and will likely test things using your method because it's just 100x easier and more realistic in terms of setting up an experiment that's possible. Also I mentioned in another comment that your experiment does not actually rule out the genetic factor. Both genetics and smoking and tar could all logically be causative factors for cancer. If the previous statement was true all your correlations established in your post would be exactly the same... there were many assumptions made. So in short your experimental evidence lends support for multiple conclusions that cannot be discounted.
  - DavidSJ 6y ago
    The comment you’re replying to addressed your concern about the genetic factor. As I said, by controlling for smoking behavior, you sever the statistical link between tar deposits and genetics in hypothesis (2+A), hence you also sever the indirect statistical link between tar deposits and cancer which is due to genetics.
    - Geminidog 6y ago
      I feel you are conflating hypothesis with logic and science your previous statement of saying: "we can always introduce new ad-hoc hypotheses, but good science isn't done willy nilly," Good science isn't restricting the entire universe to two possible hypothesis. Think about it logically. What scientist can publish a paper that says that genes don't predispose anyone to cancer or smoking because he just observed smoking correlates with tar? You literally say smoking must cause tar because it's the only possibility in your two hypothesis... one must occur. Sure if this was math and you defined your universe to be one of two possibilities... but no person in the real world will take that seriously. In math you don't introduce ad-hoc axioms and rules to your formal analysis, but the scientific method exists because all observation in the real universe is ad-hoc. Anything goes and that's why the best way to make sense of it is through correlation. Which brings me full circle back to my original method. Can you introduce any "adhoc hypothesis" to render a causation established by directly controlling the causative event invalid? You can't. Therefore the actual formal scientific way to determining causation is by placing yourself in the system. The only way the graph method can be applied to the real world is if you map out every possible scenario and assumption into that graph. Then you can say based off of what we know and assume A must cause B. But more often then not a scientist is likely just establishing some correlations and coming to a qualitative conclusion that takes into account all the assumptions and hypothesis that we're aware about in the real world.

Geminidog 6y ago

Actually under your experiment both could be still be causative factors. Determining Tar correlates with cancer does not eliminate the genetic factor. The only assumption for direct control of the hypothesized causative factor that needs to be made is that your influence on the causative factor is 100% side effect free. This is not fully possible in reality but still assuming this in your experiments allows you to arrive at a conclusion without assuming other correlations.

DavidSJ 6y ago

We're comparing two competing hypotheses to explain the correlation between smoking and cancer. Like I said, we can always introduce new ad-hoc hypotheses, but good science isn't done willy nilly, it's done with background knowledge of how the systems might plausibly work. The two hypotheses are: (1) smoking → tar → cancer (2) smoking ← genes → cancer Note that (1) contains the sub-hypothesis (A) smoking → tar, which is also compatible with (2). The super-graph containing both graphs is: ————genes———— ↓ ↓ smoking → tar → cancer In that super-graph, there is only one possible explanation for a correlation between smoking and tar: smoking causing tar. So if we see that correlation, then barring alternative hypotheses, we know the causation smoking → tar is true. (Again, we could always hypothesize other causal explanations, but we're presuming no one has yet submitted a plausible alternative explanation.) Now once smoking → tar is established, we are still left with two possible explanations for the observed correlation between smoking and cancer: (1) smoking → tar → cancer (2+A) tar ← smoking ← genes → cancer This is where controlling for smoking behavior comes in. Once we do that, we've severed the indirect statistical link between tar and cancer in graph (2+A). Thus if a correlation still persists between tar and cancer after this statistical control, we've ruled out (2+A), leaving only (1).

Geminidog 6y ago
Right I understand we're introducing new hypothesis, but it still stands. By controlling the causative factor no new hypothesis can undermine an established causation assuming that there are no side effects when we trigger a causation event. Think about it. This means that causation is actually established versus the other method which is a flimsier verification. Another way to look at it is that rather then introducing a new "hypothesis" you had to introduce assumptions about causation. You're thinking in terms of math where you can control your primitives and set a domain and range. In science none of these can be fully controlled and a "new hypothesis" does indeed apply. Think about it. If I introduce a new hypothesis in the real world that actually lends good evidence in support of say the cancer outcome I cannot just discount it and say it's not good science. You can only restrict your universe like this in the world of math and logic, in the real world you have to except any reasonable evidence that comes your way. In practice however, most scientists make a bunch of assumptions and will likely test things using your method because it's just 100x easier and more realistic in terms of setting up an experiment that's possible. Also I mentioned in another comment that your experiment does not actually rule out the genetic factor. Both genetics and smoking and tar could all logically be causative factors for cancer. If the previous statement was true all your correlations established in your post would be exactly the same... there were many assumptions made. So in short your experimental evidence lends support for multiple conclusions that cannot be discounted.
- DavidSJ 6y ago
  The comment you’re replying to addressed your concern about the genetic factor. As I said, by controlling for smoking behavior, you sever the statistical link between tar deposits and genetics in hypothesis (2+A), hence you also sever the indirect statistical link between tar deposits and cancer which is due to genetics.
  - Geminidog 6y ago
    I feel you are conflating hypothesis with logic and science your previous statement of saying: "we can always introduce new ad-hoc hypotheses, but good science isn't done willy nilly," Good science isn't restricting the entire universe to two possible hypothesis. Think about it logically. What scientist can publish a paper that says that genes don't predispose anyone to cancer or smoking because he just observed smoking correlates with tar? You literally say smoking must cause tar because it's the only possibility in your two hypothesis... one must occur. Sure if this was math and you defined your universe to be one of two possibilities... but no person in the real world will take that seriously. In math you don't introduce ad-hoc axioms and rules to your formal analysis, but the scientific method exists because all observation in the real universe is ad-hoc. Anything goes and that's why the best way to make sense of it is through correlation. Which brings me full circle back to my original method. Can you introduce any "adhoc hypothesis" to render a causation established by directly controlling the causative event invalid? You can't. Therefore the actual formal scientific way to determining causation is by placing yourself in the system. The only way the graph method can be applied to the real world is if you map out every possible scenario and assumption into that graph. Then you can say based off of what we know and assume A must cause B. But more often then not a scientist is likely just establishing some correlations and coming to a qualitative conclusion that takes into account all the assumptions and hypothesis that we're aware about in the real world.