andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1542 knowledge-graph by maker-knowledge-mining
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Introduction: We have lots of models for overdispersed count data but we rarely see underdispersed data. But now I know what example I’ll be giving when this next comes up in class. From a book review by Theo Tait: A number of shark species go in for oophagy, or uterine cannibalism. Sand tiger foetuses ‘eat each other in utero, acting out the harshest form of sibling rivalry imaginable’. Only two babies emerge, one from each of the mother shark’s uteruses: the survivors have eaten everything else. ‘A female sand tiger gives birth to a baby that’s already a metre long and an experienced killer,’ explains Demian Chapman, an expert on the subject. That’s what I call underdispersion. E(y)=2, var(y)=0. Take that, M. Poisson!
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1 We have lots of models for overdispersed count data but we rarely see underdispersed data. [sent-1, score-0.573]
2 But now I know what example I’ll be giving when this next comes up in class. [sent-2, score-0.282]
3 From a book review by Theo Tait: A number of shark species go in for oophagy, or uterine cannibalism. [sent-3, score-0.735]
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6 ‘A female sand tiger gives birth to a baby that’s already a metre long and an experienced killer,’ explains Demian Chapman, an expert on the subject. [sent-6, score-1.595]
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same-blog 1 0.99999994 1542 andrew gelman stats-2012-10-20-A statistical model for underdispersion
Introduction: We have lots of models for overdispersed count data but we rarely see underdispersed data. But now I know what example I’ll be giving when this next comes up in class. From a book review by Theo Tait: A number of shark species go in for oophagy, or uterine cannibalism. Sand tiger foetuses ‘eat each other in utero, acting out the harshest form of sibling rivalry imaginable’. Only two babies emerge, one from each of the mother shark’s uteruses: the survivors have eaten everything else. ‘A female sand tiger gives birth to a baby that’s already a metre long and an experienced killer,’ explains Demian Chapman, an expert on the subject. That’s what I call underdispersion. E(y)=2, var(y)=0. Take that, M. Poisson!
2 0.11432963 144 andrew gelman stats-2010-07-13-Hey! Here’s a referee report for you!
Introduction: I just wrote this, and I realized it might be useful more generally: The article looks reasonable to me–but I just did a shallow read and didn’t try to judge whether the conclusions are correct. My main comment is that if they’re doing a Poisson regression, they should really be doing an overdispersed Poisson regression. I don’t know if I’ve ever seen data in my life where the non-overdispersed Poisson is appropriate. Also, I’d like to see a before-after plot with dots for control cases and open circles for treatment cases and fitted regression lines drawn in. Whenever there’s a regression I like to see this scatterplot. The scatterplot isn’t a replacement for the regression, but at the very least it gives me intuition as to the scale of the estimated effect. Finally, all their numbers should be rounded appropriately. Feel free to cut-and-paste this into your own referee reports (and to apply these recommendations in your own applied research).
3 0.080515265 1734 andrew gelman stats-2013-02-23-Life in the C-suite: A graph that is both ugly and bad, and an unrelated story
Introduction: Jemes Keirstead sends along this infographic : He hates it: First we’ve got an hourglass metaphor wrecked by the fact that “now” (i.e. the pinch point in the glass) is actually 3-5 years in the future and the past sand includes “up to three years” in the future. Then there are the percentages which are appear to represent a vertical distance, not volume of sand or width of the hourglass. Add to that a strange color scheme in which green goes from dark to light to dark again. I know January’s not even finished yet, but surely a competitor for worst infographic of 2013? Keirstead doesn’t even comment on what I see as the worst aspect of the graph, which is that the “3-5 years” band is the narrowest on the graph, but expressed as a per-year rate it is actually the highest of all the percentages. The hourglass visualization does the astounding feat of taking the period where the executives expect the highest rate of change and presenting it as a minimum in the graph.
4 0.07736782 1494 andrew gelman stats-2012-09-13-Watching the sharks jump
Introduction: Recently in the sister blog: Niall Ferguson is a hack . Niall Ferguson is not always a hack, sometimes he just makes silly mistakes . Paul Krugman is not a hack, but he sometimes he goes over the top . Reflections on hacks . P.S. Yes, technically I’m misusing the expression, it should really be something like, “Watching the sharks get jumped.” But I liked the image of the jumping shark.
5 0.070653498 1294 andrew gelman stats-2012-05-01-Modeling y = a + b + c
Introduction: Brandon Behlendorf writes: I [Behlendorf] am replicating some previous research using OLS [he's talking about what we call "linear regression"---ed.] to regress a logged rate (to reduce skew) of Y on a number of predictors (Xs). Y is the count of a phenomena divided by the population of the unit of the analysis. The problem that I am encountering is that Y is composite count of a number of distinct phenomena [A+B+C], and these phenomena are not uniformly distributed across the sample. Most of the research in this area has conducted regressions either with Y or with individual phenomena [A or B or C] as the dependent variable. Yet it seems that if [A, B, C] are not uniformly distributed across the sample of units in the same proportion, then the use of Y would be biased, since as a count of [A+B+C] divided by the population, it would treat as equivalent units both [2+0.5+1.5] and [4+0+0]. My goal is trying to find a methodology which allows a researcher to regress Y on a
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same-blog 1 0.92126822 1542 andrew gelman stats-2012-10-20-A statistical model for underdispersion
Introduction: We have lots of models for overdispersed count data but we rarely see underdispersed data. But now I know what example I’ll be giving when this next comes up in class. From a book review by Theo Tait: A number of shark species go in for oophagy, or uterine cannibalism. Sand tiger foetuses ‘eat each other in utero, acting out the harshest form of sibling rivalry imaginable’. Only two babies emerge, one from each of the mother shark’s uteruses: the survivors have eaten everything else. ‘A female sand tiger gives birth to a baby that’s already a metre long and an experienced killer,’ explains Demian Chapman, an expert on the subject. That’s what I call underdispersion. E(y)=2, var(y)=0. Take that, M. Poisson!
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Introduction: This looks cool: Ten years ago researchers in America took two groups of three-year-olds and showed them a blob of paint on a canvas. Children who were told that the marks were the result of an accidental spillage showed little interest. The others, who had been told that the splodge of colour had been carefully created for them, started to refer to it as “a painting”. Now that experiment . . . has gone on to form part of the foundation of an influential new book that questions the way in which we respond to art. . . . The book, which is subtitled The New Science of Why We Like What We Like, is not an attack on modern or contemporary art and Bloom says fans of more traditional art are not capable of making purely aesthetic judgments either. “I don’t have a strong position about the art itself,” he said this weekend. “But I do have a strong position about why we actually like it.” This sounds fascinating. But I’m skeptical about this part: Humans are incapable of just getti
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Introduction: In her essay on Margaret Mitchell and Gone With the Wind, Claudia Roth Pierpoint writes: The much remarked “readability” of the book must have played a part in this smooth passage from the page to the screen, since “readability” has to do not only with freedom from obscurity but, paradoxically, with freedom from the actual sensation of reading [emphasis added]—of the tug and traction of words as they move thoughts into place in the mind. Requiring, in fact, the least reading, the most “readable” book allows its characters to slip easily through nets of words and into other forms. Popular art has been well defined by just this effortless movement from medium to medium, which is carried out, as Leslie Fiedler observed in relation to Uncle Tom’s Cabin, “without loss of intensity or alteration of meaning.” Isabel Archer rises from the page only in the hanging garments of Henry James’s prose, but Scarlett O’Hara is a free woman. Well put. I wish Pierpoint would come out with ano
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Introduction: Hermann Goering is famous for two things: 1. Being an air force general, and 2. Being a really bad air force general. What does this have to do, you may ask, with Jane Jacobs, who is famous for a book she wrote in the early 1960s advocating small, mixed-use street-level city development, in contrast to the mega-projects that were advocated by many influential planners at the time. The connection is, as a London-based friend pointed out to me the other day, that the German bombing of London in WW2 knocked out random sections all over the city, which were then often replaced by various public developments. The knocked-out portions were often small, so there was not always room for megablocks to replace them, and they were scattered—so the new housing was also distributed haphazardly all over the city. Thus, Goering helped in two ways, corresponding to the two numbered points listed above: 1. His air force dropped bombs and destroyed buildings all over London. 2. His at
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Introduction: This blog is threatening to turn into Statistical Modeling, Causal Inference, Social Science, and Literature Criticism, but I’m just going to go with the conversational flow, so here’s another post about an essayist. I’m not a big fan of Janet Malcolm’s essays — and I don’t mean I don’t like her attitude or her pro-murderer attitude, I mean I don’t like them all that much as writing. They’re fine, I read them, they don’t bore me, but I certainly don’t think she’s “our” best essayist. But that’s not a debate I want to have right now, and if I did I’m quite sure most of you wouldn’t want to read it anyway. So instead, I’ll just say something about John McPhee. As all right-thinking people agree, in McPhee’s long career he has written two kinds of books: good, short books, and bad, long books. (He has also written many New Yorker essays, and perhaps other essays for other magazines too; most of these are good, although I haven’t seen any really good recent work from him, and so
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1 0.91432929 891 andrew gelman stats-2011-09-05-World Bank data now online
Introduction: Wayne Folta writes that the World Bank is opening up some of its data for researchers.
same-blog 2 0.89623272 1542 andrew gelman stats-2012-10-20-A statistical model for underdispersion
Introduction: We have lots of models for overdispersed count data but we rarely see underdispersed data. But now I know what example I’ll be giving when this next comes up in class. From a book review by Theo Tait: A number of shark species go in for oophagy, or uterine cannibalism. Sand tiger foetuses ‘eat each other in utero, acting out the harshest form of sibling rivalry imaginable’. Only two babies emerge, one from each of the mother shark’s uteruses: the survivors have eaten everything else. ‘A female sand tiger gives birth to a baby that’s already a metre long and an experienced killer,’ explains Demian Chapman, an expert on the subject. That’s what I call underdispersion. E(y)=2, var(y)=0. Take that, M. Poisson!
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Introduction: Wayne Folta points us to this list .
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Introduction: Diederik Stapel gives a Ted talk . Sometimes, reality truly is a parody of reality.
Introduction: That’s ok , Krugman earlier slammed Galbraith. (I wonder if Krugman is as big a fan of “tough choices” now as he was in 1996 .) Given Krugman’s politicization in recent years, I’m surprised he’s so dismissive of the political (rather than technical-economic) nature of Hayek’s influence. (I don’t know if he’s changed his views on Galbraith in recent years.) P.S. Greg Mankiw, in contrast, labels Galbraith and Hayek as “two of the great economists of the 20th century” and writes, “even though their most famous works were written many decades ago, they are still well worth reading today.”
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