Sunday data/statistics link roundup (12/15/13)

  1. Rafa (in Spanish) clarifying some of the problems with the anti-GMO crowd.
  2. Joe Bliztstein, most recently of #futureofstats fame, talks up data science in the Harvard Crimson (via Rafa). As has been pointed out by Rebecca Nugent when she stopped to visit us, class sizes in undergrad stats programs are blowing up!
  3. If you missed it, Michael Eisen dropped by to chat about open access (part 1/part 2). We talked about Randy Schekman, a recent Nobel prize winner who says he isn't publishing in Nature/Science/Cell anymore. Professor Schekman did a Reddit AMA where he got grilled pretty hard about pushing a glamour open access journal eLife, while dissing N/S/C, where he published a lot of stuff before winning the Nobel.
  4. The article I received most the last couple of weeks is this one. In it, Peter Higgs says he wouldn't have had time to think deeply to perform the research that led to the Boson discovery in the modern publish or perish academic system. But he got the prize, at least in part, because of the people who conceived/built/tested the theory in the Large Hadron Collider. I'm much more inclined to believe someone would have come up with the Boson theory in our current system than someone would have built the LHC in a system without competitive pressure.
  5. I think this post raises some interesting questions about the Obesity Paradox that says overweight people with diabetes may have lower risk of death than normal weight people. The analysis is obviously tongue-in-cheek, but I'd be interested to hear what other people think about whether it is a serious issue or not.
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  • Lucas

    About Obesity Paradox: what if obesity is actually a body defense mechanism against diabetes? There are more and more evidence everyday showing that high blood sugar causes both diabetes and obesity. That would not be an absurd, and would explain the paradox.

  • Julian Wolfson

    #5 is an interesting post, but unfortunately the author doesn't really have a good understanding of regression adjustment so the analysis and criticism of the source JAMA article is a bit simplistic.

    The obesity paradox is an interesting phenomenon which obviously has yet to be fully characterized. I suspect that it's driven by some combination of selection bias in the observational data and a few latent factors (some genetic, some physiological, some behavioral) that we haven't been able to adequately measure.

  • TwentyLYS

    #5: Conclusion: Adults who were normal weight at the time of incident diabetes had higher mortality than adults who are overweight or obese.

    Very Interesting conclusion, worth reading thoroughly and for sure I will.

  • Jack

    Regarding #2 - I've been out of my undergrad and working for about 2 years now. I loved undergrad stats - I took all 3 courses - and I feel like it has definitely given me an edge in finding employment, as I get to apply the skills learned every day. I've taken a lot of time to evaluate the direction in which I want my career to go, and have decided that an Msc. in Stats or Applied is something I am really interested in pursuing, particularly in the area of Scientific Computing.

    I guess this may be an irrational concern, but this sudden influx of new undergraduates seems like it will make it much more competitive to find a program. The hype around stats and data seems like it will produce a large cohort, which is excellent for the field, but might make things difficult on me when it comes to choosing someone coming directly from undergrad vs. myself coming back to school from the workforce.

    Is this a valid concern in your opinion(s)?

    Should I avoid wasting any more time and get to applyin'?

    Thanks for reading!

  • Jeffrey Walker

    Sure, I'll bite. Be kind. I'm not a statistician. Create a DAG with BMI=X, WAIST=Z, and Mortality =Y (the response). The trait ABD_FAT has directed arrows to BMI, WAIST, and Mortality. The trait NON_ABD_FAT has directed arrows to BMI and mortality. If BMI is conditioned on WAIST, this effectively removes ABD_FAT as a causal factor on mortality, which is certainly not the intent of the authors and I think what the poster was getting at. Pearl has talked about this many places but see here: