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Martin Luther King (2) vs. Sigmund Freud

We didn’t get any great comments yesterday, so I’ll have to go with PKD on the grounds that he was the presumptive favorite, and nobody made any good case otherwise.

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And today we have the second seed among the Religious Leaders vs. an unseeded entry in the Founders of Religions category. Truly a classic matchup. MLK perhaps has the edge here because he can talk about plagiarism; on the other hand, Freud is an expert in unfalsifiable research theories. I imagine that either one would be an amazingly compelling speaker. King would have a lot to say about Middle East wars, globalization, and economic and social inequality; and Freud could wittily diagnose all of society’s problems. I’d love to have them both—but that’s not allowed. So who’s it gonna be?

P.S. As always, here’s the background, and here are the rules.

“Unbiasedness”: You keep using that word. I do not think it means what you think it means. [My talk tomorrow in the Princeton economics department]


The talk is tomorrow, Tues 24 Feb, 2:40-4:00pm in 200 Fisher Hall:

“Unbiasedness”: You keep using that word. I do not think it means what you think it means.

Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University

Minimizing bias is the traditional first goal of econometrics. In many cases, though, the goal of unbiasedness can lead to extreme claims that are both substantively implausible and not supported by data. We illustrate with several examples in areas ranging from public opinion to social psychology to public heath, using methods including regression discontinuity, hierarchical models, interactions in regression, and data aggregation. Methods that purport to be unbiased, aren’t, once we carefully consider inferential goals and select on the analyses that are actually performed and reported. The implication for econometrics research: It’s best to be aware of all sources of error, rather than to focus narrowly on reducing bias with respect to one particular aspect of your model.

This work reflects collaboration with Guido Imbens and others. Here are the slides, and people can read the following papers for partial background:

Why high-order polynomials should not be used in regression discontinuity designs. (Andrew Gelman and Guido Imbens)

[2015] Evidence on the deleterious impact of sustained use of polynomial regression on causal inference. Research and Politics. (Andrew Gelman and Adam Zelizer)

[2014] Beyond power calculations: Assessing Type S (sign) and Type M (magnitude) errors. Perspectives on Psychological Science 9, 641-651. (Andrew Gelman and John Carlin)

On deck this week

Mon: “Unbiasedness”: You keep using that word. I do not think it means what you think it means. [My talk tomorrow in the Princeton economics department]

Martin Luther King (2) vs. Sigmund Freud

Tues: “A small but growing collection of studies suggest X” . . . huh?

Aristotle (3) vs. Stewart Lee

Wed: The axes are labeled but I don’t know what the dots represent.

Abraham (4) vs. Jane Austen

Thurs: In criticism of criticism of criticism

Richard Pryor (1) vs. Karl Popper

Fri: “The harm done by tests of significance” (article from 1994 in the journal, “Accident Analysis and Prevention”)

William Shakespeare (1) vs. Karl Marx

Sat: Forget about pdf: this looks much better, it makes all my own papers look like kids’ crayon drawings by comparison

Friedrich Nietzsche (4) vs. Alan Bennett

Sun: Time-release pedagogy??

Buddha (3) vs. John Updike

Philip K. Dick (2) vs. Jean Baudrillard

For yesterday, I was gonna go with Vincent, based on X’s comment:

In addition to his unique painting style and very special life, van Gogh was highly literate, as shown through the 844 letters from him that are available today.

X also made a missing-body-part joke, which I generally don’t think is so cool but, if anyone’s allowed to get away with that sort of humor, it’s X.

Anyway, now I was curious so I googled *Vincent Van Gogh letters* and found this site. I clicked through and looked at a few letters and they seemed like nothing special.

So, given that this was the best argument in favor and it wasn’t so great, I’ll have to call it for Grandma Moses, boring as she sounds.


Today we have Horselover Fat vs. the self-parodying intellectual. Dick would seem to be the easy winner here. But Baudrillard did write this:

Decidedly, joggers are the true Latter Day Saints and the protagonists of an easy-does-it Apocalypse. Nothing evokes the end of the world more than a man running straight ahead on a beach, swathed in the sounds of his walkman, cocooned in the solitary sacrifice of his energy, indifferent even to catastrophes since he expects destruction to come only as the fruit of his own efforts, from exhausting the energy of a body that has in his own eyesbecome useless. Primitives, when in despair, would commit suicide by swimming out to sea until they could swim no longer. The jogger commits suicide by running up and down the beach. His eyes are wild, saliva drips from his mouth. Do not stop him. He will either hit you or simply carry on dancing around in front of you like a man possessed.

I think we can safely say this is a contest between two guys who did not spend much time at the gym.

P.S. As always, here’s the background, and here are the rules.

“Academics should be made accountable for exaggerations in press releases about their own work”

Fernando Martel Garcia points me to this news article by Ben Goldacre:

For anyone with medical training, mainstream media coverage of science can be an uncomfortable read. It is common to find correlational findings misrepresented as denoting causation, for example, or findings in animal studies confidently exaggerated to make claims about treatment for humans. But who is responsible for these misrepresentations?

In the linked paper (doi:10.1136/bmj.g7015) Sumner and colleagues found that much of the exaggeration in mainstream media coverage of health research—statements that went beyond findings in the academic paper—was already present in the press release sent out to journalists by the academic institution itself.

Sumner and colleagues identified all 462 press releases on health research from 20 leading UK universities over one year. They traced 668 associated news stories . . .

The story is pretty much as you’d predict: a lot of the exaggeration comes in the press release.

I remarked that this makes sense. I agree. Of course, this is just a start, as I’m sure a lot of academics would be happy to put their names on various exaggerated claims! See, for example, here, where the researchers in question were very active with the publicity, and in which they dramatically overstated the implications on individual-level behavior that could be drawn from their state-level analysis. The lead research in this case was just a law professor, but still, we’d like to see better.

As this example illustrates, the problem is not necessarily any sort of conscious exaggeration or hype: I assume that the researchers in question really believe that their claims are supported by their data. For that matter, I assume that disgraced primatologist Mark Hauser really believes his theories.

To put it another reason: be skeptical of press releases, not because they’re written by sleazy public relations people, but because they’re written by, or with the collaboration, of researchers who know enough to make a superficially convincing case but not enough to recognize the flaws in their reasoning.

Vincent van Gogh (3) vs. Grandma Moses

In yesterday‘s battle of the religions, the strongest argument against Mother Teresa was given by Paul, who related that she was friends with all sorts of nasty politicians and that she’s been accused of spending money that came from questionable sources. But if that’s all you can say about her, it won’t cut much ice with Sun Myung Moon, who also was friends with various unsavory characters and scammed all sorts of money. So Moon is more of a badass. But this isn’t a contest about who’s the toughest guy—we’re looking for a seminar speaker here, not a rogue sociologist.

I’ll have to with Mother Teresa. I doubt we’ll see any faith healings but I’m persuaded by Ken’s negative case against Moon:

Moon’s wikipedia page describes him as a “religious leader, businessperson, political activist, and media mogul.” In my experience people with “rock star” status like this make for bad seminar speakers because they tend to be full of anecdotes and fluff, and light on rigorous empirical evidence.

Good point. The last thing we need here is a goddam Ted talk.


And today we have a contest between two artists! Vincent is more famous and would certainly be the bigger draw, but I wouldn’t be surprised if Grandma could give a more coherent lecture. On the other hand, according to wikipedia, “she was a Society of Mayflower Descendants and Daughters of the American Revolution member.” And that sounds pretty duuuulllllllll. It’s up to all of you to make the strongest and wittiest arguments on both sides.

P.S. As always, here’s the background, and here are the rules.

Bayes and doomsday

Ben O’Neill writes:

I am a fellow Bayesian statistician at the University of New South Wales (Australia).  I have enjoyed reading your various books and articles, and enjoyed reading your recent article on The Perceived Absurdity of Bayesian Inference.  However, I disagree with your assertion that the “doomsday argument” is non-Bayesian; I think if you read how it is presented by Leslie you will see that it is at least an attempt at a Bayesian argument.  In any case, although it has enough prima facie plausibility to trick people, the argument is badly flawed, and not a correct application of Bayesian reasoning.  I don’t think it is a noose around the Bayesian neck.

Anyway, I’m just writing because I thought you might be interested in a recent paper on this topic in the Journal of Philosophy.  The paper is essentially a Bayesian refutation of the doomsday argument, pointing out how it goes wrong, and how it is an incorrect application of Bayesian inference.  (And also how a correct application of Bayesian inference leads to sensible conclusions.)  Essentially, the argument confuses total series length with remaining series length, and sneaks information from the data into the prior in a way which is invalid.  Once this is corrected the absurd conclusions of the doomsday argument evaporate.

I don’t really have anything more to say on this topic (here’s my argument from 2005 as to why I think the doomsday argument is clearly frequentist and not particularly Bayesian) but I thought some of you might be interested, hence the pointer.

The bracket so far

Thanks to the Excel stylings of Paul Davidson:


Our competition is (approximately) 1/4 done!

And I’ve been thinking about possible categories for next year’s tourney:

New Jersey politicians
Articulate athletes
People named Greg or Gregg
Vladimir Nabokov and people connected to him
. . .

Ummm, we need 3 more categories. Any suggestions? Real people only, please. In some future year we can have an all-fictional category.

Mother Teresa (4) vs. Sun Myung Moon

For yesterday, I’ll have to go with Gandhi, the original badass of nonviolence. Zbicyclist found this quote, “He propagated that . . . we should take only that which is required, in minimum quantity. We should not eat to appease our taste buds,” which implies that Gandhi shouldn’t pick the caterer—but that’s not an issue, we never have any special food with our seminars anyway.

Jonathan argued in favor of Kubrick based on this quote: “Well, you don’t make it easy on viewers or critics. You’ve said you want an audience to react emotionally. You create strong feelings, but you won’t give us any easy answers. That’s because I don’t have any easy answers.”

But, as a Bayesian, I do want easy answers, so this line of argument doesn’t work for me.


And now for today we have two people who’ve done a lot, but might not be very articulate seminar speakers. The nun is seeded #4 in the Religious Leaders category; Sun Myung Moon is listed under Cult Figures. For sheer spectacle, ya gotta go with the Moonies. On the other hand, with Mother Teresa we might see a documented miracle. According to Wikipedia, “In 2002, the Vatican recognised as a miracle the healing of a tumor in the abdomen of an Indian woman, Monica Besra, after the application of a locket containing Mother Teresa’s picture.”

It’s been 13 years, so maybe Teresa is up for another miraculous cure?

P.S. As always, here’s the background, and here are the rules.

Statistical Significance – Significant Problem?

John Carlin, who’s collaborated on some of my recent work on Type S and Type M errors, prepared this presentation for a clinical audience. It might be of interest to some of you. The ideas and some of the examples should be familiar to regular readers of this blog, but it could be useful to see how this material is presented to a different sort of group than I usually encounter.