IlyaShpitser comments on Results of a One-Year Longitudinal Study of CFAR Alumni - LessWrong

33 Post author: Unnamed 12 December 2015 04:39AM

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Comment author: IlyaShpitser 15 December 2015 07:21:25AM *  0 points [-]

Yes, M-bias is an example of a situation where a variable depends on treatment and outcome, but is not a confounder. Hence I was confused by your statement:

confounding depends on the correlations with both the independent and dependent variables

Confounding is not about that at all.

Comment author: AstraSequi 16 December 2015 04:25:14AM *  0 points [-]

I used "depends" informally, so I didn't mean to say that variables that depend on treatment and outcome are always confounders. I was answering the implication that a variable with no detectable correlation with the outcome is not likely to be a source of confounding. I assumed they were using a correlational definition of confounding, so I answered in that context.

Comment author: IlyaShpitser 16 December 2015 04:30:49AM *  2 points [-]

Should be careful with that, might confuse people, see also:

https://en.wikipedia.org/wiki/Confounding

which gets it wrong.


A variable with no detectable correlation with the outcome might still be a confounder, of course, you might have unfaithful things going on, or dependence might be non-linear. "Unlikely" usually implies "with respect to some model" you have in mind. How do you know that model is right? What if the true model is highly unfaithful for some reason? etc. etc.


edit: I don't mean to jump on you specifically, but it sort of is unfortunate that it somehow is a social norm to say wrong things in statistics "informally." To me, that's sort of like saying "don't worry, when I said 2+2=5, I was being informal."

Comment author: AstraSequi 18 December 2015 02:29:25AM 1 point [-]

To me, that's sort of like saying "don't worry, when I said 2+2=5, I was being informal."

Very true. This is something I'll try to change.

Comment author: IlyaShpitser 18 December 2015 03:45:56PM *  1 point [-]

Cheers! If you know what M-bias is, we must have hung out in similar circles. Where did you learn "the causal view of epi"?

Comment author: ChristianKl 18 December 2015 04:06:45PM 0 points [-]

Should be careful with that, might confuse people, see also:

https://en.wikipedia.org/wiki/Confounding

which gets it wrong.

If Wikipedia get's it wrong it might be high leverage to correct it.

Comment author: IlyaShpitser 18 December 2015 04:11:17PM *  1 point [-]

We talked about this before. I disagree with wikipedia's philosophy, and don't have time to police edits there. Wikipedia doesn't have a process in place to recognize that the opinion of someone like me on a subject like confounding is worth considerably more than the opinion of a randomly sampled internet person. I like *overflow a lot better.


One somewhat subtle point in that article is that it is titled "confounding" (which is easy to define), but then tries to define "a confounder" which is much harder, and might not be a well-defined concept according to some people.