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Lumifer comments on Open Thread, April 27-May 4, 2014 - Less Wrong Discussion

0 Post author: NancyLebovitz 27 April 2014 08:34PM

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Comment author: IlyaShpitser 02 May 2014 04:33:41PM *  1 point [-]

I don't know how Metamed works (and it's sort of their secret sauce, so they probably will not tell us without an NDA). I am guessing it is some combination of doing (a) through (e) above for someone who cannot do it themselves, and possibly some B stats. Which seems like a perfectly sensible business model to me!

I don't think the secret sauce is in the B stats part of what they are doing, though. If we had a hypothetical company called "Freqmed" that also humanwaved (a) through (e), and then used F stats I doubt they would get non-sensible answers. It's about being sensible, not your identity as a statistician.


I can be F with Bayes nets. Bayes nets are just a conditional independence model.


I don't know how successful Metamed will be, but I honestly wish them the best of luck. I certainly think there is a lot of crazy out there in data analysis, and it's a noble thing to try to make money off of making things more sensible.


The thing is, I don't know about a lot of the things that get talked about on LW. I do know about B and F a little bit, and about causality a little bit. And a huge chunk of stuff people say is just plain wrong. So I tell them it's wrong, but they keep going and don't change what they say at all. So how should I update -- that folks on this rationalist community generally don't know what they are talking about and refuse to change?

It's like wikipedia -- the first sentence in the article on confounders is wrong on wikipedia (there is a very simple 3 node example that violates that definition). The talk page on Bayesian networks is a multi-year tale of woe and ignorance. I once got into an edit war with a resident bridge troll for that article, and eventually gave up and left, because he had more time. What does that tell me about wikipedia?

Comment author: Lumifer 02 May 2014 04:47:17PM *  2 points [-]

It's about being sensible, not your identity as a statistician.

Speaking of, an interesting paper which distinguishes the Fisher approach to testing from the Neyman-Pearson approach and shows how you can unify/match some of that with Bayesian methods.