andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2019 knowledge-graph by maker-knowledge-mining

2019 andrew gelman stats-2013-09-12-Recently in the sister blog


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Introduction: Don’t be so quick to place politicians’ views of “national interests” above the mood of the public More on those pollsters who apparently throw away completed survey responses A theory of the importance of Very Serious People in the Democratic Party Mother–child conversations about pictures and objects: Referring to categories and individuals


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same-blog 1 0.99999994 2019 andrew gelman stats-2013-09-12-Recently in the sister blog

Introduction: Don’t be so quick to place politicians’ views of “national interests” above the mood of the public More on those pollsters who apparently throw away completed survey responses A theory of the importance of Very Serious People in the Democratic Party Mother–child conversations about pictures and objects: Referring to categories and individuals

2 0.11550044 2103 andrew gelman stats-2013-11-16-Objects of the class “Objects of the class”

Introduction: Objects of the class “Foghorn Leghorn” : parodies that are more famous than the original. (“It would be as if everybody were familiar with Duchamp’s Mona-Lisa-with-a-moustache while never having heard of Leonardo’s version.”) Objects of the class “Whoopi Goldberg” : actors who are undeniably talented but are almost always in bad movies, or at least movies that aren’t worthy of their talent. (The opposite: William Holden.) Objects of the class “Weekend at Bernie’s” : low-quality movie, nobody’s actually seen it, but everybody knows what it’s about. (Other examples: Heathers and Zelig.) I love these. We need some more.

3 0.11522894 574 andrew gelman stats-2011-02-14-“The best data visualizations should stand on their own”? I don’t think so.

Introduction: Jimmy pointed me to this blog by Drew Conway on word clouds. I don’t have much to say about Conway’s specifics–word clouds aren’t really my thing, but I’m glad that people are thinking about how to do them better–but I did notice one phrase of his that I’ll dispute. Conway writes The best data visualizations should stand on their own . . . I disagree. I prefer the saying, “A picture plus 1000 words is better than two pictures or 2000 words.” That is, I see a positive interaction between words and pictures or, to put it another way, diminishing returns for words or pictures on their own. I don’t have any big theory for this, but I think, when expressed as a joint value function, my idea makes sense. Also, I live this suggestion in my own work. I typically accompany my graphs with long captions and I try to accompany my words with pictures (although I’m not doing it here, because with the software I use, it’s much easier to type more words than to find, scale, and insert i

4 0.11295036 1744 andrew gelman stats-2013-03-01-Why big effects are more important than small effects

Introduction: The title of this post is silly but I have an important point to make, regarding an implicit model which I think many people assume even though it does not really make sense. Following a link from Sanjay Srivastava, I came across a post from David Funder saying that it’s useful to talk about the sizes of effects (I actually prefer the term “comparisons” so as to avoid the causal baggage) rather than just their signs. I agree , and I wanted to elaborate a bit on a point that comes up in Funder’s discussion. He quotes an (unnamed) prominent social psychologist as writing: The key to our research . . . [is not] to accurately estimate effect size. If I were testing an advertisement for a marketing research firm and wanted to be sure that the cost of the ad would produce enough sales to make it worthwhile, effect size would be crucial. But when I am testing a theory about whether, say, positive mood reduces information processing in comparison with negative mood, I am worried abou

5 0.11129536 531 andrew gelman stats-2011-01-22-Third-party Dream Ticket

Introduction: Who are the only major politicians who are viewed more positively than negatively by the American public? (See page 3 of this report .)

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9 0.08348985 131 andrew gelman stats-2010-07-07-A note to John

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17 0.069466598 426 andrew gelman stats-2010-11-22-Postdoc opportunity here at Columbia — deadline soon!

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Introduction: Don’t be so quick to place politicians’ views of “national interests” above the mood of the public More on those pollsters who apparently throw away completed survey responses A theory of the importance of Very Serious People in the Democratic Party Mother–child conversations about pictures and objects: Referring to categories and individuals

2 0.64476752 761 andrew gelman stats-2011-06-13-A survey’s not a survey if they don’t tell you how they did it

Introduction: Since we’re on the topic of nonreplicable research . . . see here (link from here ) for a story of a survey that’s so bad that the people who did it won’t say how they did it. I know too many cases where people screwed up in a survey when they were actually trying to get the right answer, for me to trust any report of a survey that doesn’t say what they did. I’m reminded of this survey which may well have been based on a sample of size 6 (again, the people who did it refused to release any description of methodology).

3 0.64259952 113 andrew gelman stats-2010-06-28-Advocacy in the form of a “deliberative forum”

Introduction: John Sides reports on a paper by Benjamin Page and Lawrence Jacobs about so-called deliberative forums, in particular a set of meetings called America Speaks that have been organized and conducted by the Peter G. Peterson Foundation, an organization formed by the former advertising executive, Secretary of Commerce, and investment banker to focus attention on the national debt. Sides, Page, and Jacobs discuss three key points: 1. Any poll or focus group is only as good as its sample, and there is no evidence that the participants in the America Speaks forums were selected in a way to be representative of the nation. Page and Jacobs write: Deliberative forums often fail to get a representative sample of Americans to participate, even when they try hard to do so. Worse, some deliberative forums make little or no serious effort to achieve representativeness. They throw open the doors to self-selected political activists with extreme opinions, or they compile a secret list

4 0.59431267 130 andrew gelman stats-2010-07-07-A False Consensus about Public Opinion on Torture

Introduction: John Sides reports on this finding by Paul Gronke, Darius Rejali, Dustin Drenguis, James Hicks, Peter Miller, and Bryan Nakayama, from a survey in 2008:: Gronke et al. write (as excerpted by Sides): Many journalists and politicians believe that during the Bush administration, a majority of Americans supported torture if they were assured that it would prevent a terrorist attack….But this view was a misperception…we show here that a majority of Americans were opposed to torture throughout the Bush presidency…even when respondents were asked about an imminent terrorist attack, even when enhanced interrogation techniques were not called torture, and even when Americans were assured that torture would work to get crucial information. Opposition to torture remained stable and consistent during the entire Bush presidency. Gronke et al. attribute confusion of beliefs to the so-called false consensus effect studied by cognitive psychologists, in which people tend to assume th

5 0.59027439 977 andrew gelman stats-2011-10-27-Hack pollster Doug Schoen illustrates a general point: The #1 way to lie with statistics is . . . to just lie!

Introduction: Everybody knows how you can lie with statistics by manipulating numbers, making inappropriate comparisons, misleading graphs, etc. But, as I like to remind students, the simplest way to lie with statistics is to just lie! You see this all the time, advocates who make up numbers or present numbers with such little justification that they might as well be made up (as in this purported survey of the “super-rich”). Here I’m not talking about the innumeracy of a Samantha Power or a David Runciman, or Michael Barone-style confusion or Gregg Easterbrook-style cluelessness or even Tucker Carlson-style asininity . No, I’m talking about flat-out lying by a professional who has the numbers and deliberately chooses to misrepresent them. The culprit is pollster Doug Schoen, and the catch was made by Jay Livingston. Schoen wrote the following based on a survey he took of Occupy Wall Street participants: On Oct. 10 and 11, Arielle Alter Confino, a senior researcher at my polli

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Introduction: Don’t be so quick to place politicians’ views of “national interests” above the mood of the public More on those pollsters who apparently throw away completed survey responses A theory of the importance of Very Serious People in the Democratic Party Mother–child conversations about pictures and objects: Referring to categories and individuals

2 0.96934426 1896 andrew gelman stats-2013-06-13-Against the myth of the heroic visualization

Introduction: Alberto Cairo tells a fascinating story about John Snow, H. W. Acland, and the Mythmaking Problem: Every human community—nations, ethnic and cultural groups, professional guilds—inevitably raises a few of its members to the status of heroes and weaves myths around them. . . . The visual display of information is no stranger to heroes and myth. In fact, being a set of disciplines with a relatively small amount of practitioners and researchers, it has generated a staggering number of heroes, perhaps as a morale-enhancing mechanism. Most of us have heard of the wonders of William Playfair’s Commercial and Political Atlas, Florence Nightingale’s coxcomb charts, Charles Joseph Minard’s Napoleon’s march diagram, and Henry Beck’s 1933 redesign of the London Underground map. . . . Cairo’s goal, I think, is not to disparage these great pioneers of graphics but rather to put their work in perspective, recognizing the work of their excellent contemporaries. I would like to echo Cairo’

3 0.96796387 1299 andrew gelman stats-2012-05-04-Models, assumptions, and data summaries

Introduction: I saw an analysis recently that I didn’t like. I won’t go into the details, but basically it was a dose-response inference, where a continuous exposure was binned into three broad categories (terciles of the data) and the probability of an adverse event was computed for each tercile. The effect and the sample size was large enough that the terciles were statistically-significantly different from each other in probability of adverse event, with the probabilities increasing from low to mid to high exposure, as one would predict. I didn’t like this analysis because it is equivalent to fitting a step function. There is a tendency for people to interpret the (arbitrary) tercile boundaries as being meaningful thresholds even though the underlying dose-response relation has to be continuous. I’d prefer to start with a linear model and then add nonlinearity from there with a spline or whatever. At this point I stepped back and thought: Hey, the divide-into-three analysis does not lite

4 0.96079552 168 andrew gelman stats-2010-07-28-Colorless green, and clueless

Introduction: Faithful readers will know that my ideal alternative career is to be an editor in the Max Perkins mold. If not that, I think I’d enjoy being a literary essayist, someone like Alfred Kazin or Edmund Wilson or Louis Menand, who could write about my favorite authors and books in a forum where others would read and discuss what I wrote. I could occasionally collect my articles into books, and so on. On the other hand, if I actually had such a career, I wouldn’t have much of an option to do statistical research in my spare time, so I think for my own broader goals, I’ve gotten hold of the right side of the stick. As it is, I enjoy writing about literary matters but it never quite seems worth spending the time to do it right. (And, stepping outside myself, I realize that I have a lot more to offer the world as a statistician than literary critic. Criticism is like musicianship–it can be hard to do, and it’s impressive when done well, but a lot of people can do it. Literary criticism

5 0.95305896 269 andrew gelman stats-2010-09-10-R vs. Stata, or, Different ways to estimate multilevel models

Introduction: Cyrus writes: I [Cyrus] was teaching a class on multilevel modeling, and we were playing around with different method to fit a random effects logit model with 2 random intercepts—one corresponding to “family” and another corresponding to “community” (labeled “mom” and “cluster” in the data, respectively). There are also a few regressors at the individual, family, and community level. We were replicating in part some of the results from the following paper : Improved estimation procedures for multilevel models with binary response: a case-study, by G Rodriguez, N Goldman. (I say “replicating in part” because we didn’t include all the regressors that they use, only a subset.) We were looking at the performance of estimation via glmer in R’s lme4 package, glmmPQL in R’s MASS package, and Stata’s xtmelogit. We wanted to study the performance of various estimation methods, including adaptive quadrature methods and penalized quasi-likelihood. I was shocked to discover that glmer

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