andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1951 knowledge-graph by maker-knowledge-mining
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Introduction: Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. I would be really curious to know your list too? Scarily enough I can’t think of any truly influential papers from that decade. I suppose this means I’m getting old! P.S. I did once make a list of the top 5 unpublished papers in statistics .
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1 Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. [sent-1, score-1.191]
2 Scarily enough I can’t think of any truly influential papers from that decade. [sent-3, score-1.19]
3 I did once make a list of the top 5 unpublished papers in statistics . [sent-7, score-1.317]
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same-blog 1 1.0 1951 andrew gelman stats-2013-07-22-Top 5 stat papers since 2000?
Introduction: Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. I would be really curious to know your list too? Scarily enough I can’t think of any truly influential papers from that decade. I suppose this means I’m getting old! P.S. I did once make a list of the top 5 unpublished papers in statistics .
2 0.22619632 128 andrew gelman stats-2010-07-05-The greatest works of statistics never published
Introduction: The other day I came across a paper that referred to Charlie Geyer’s 1991 paper, “Estimating Normalizing Constants and Reweighting Mixtures in Markov Chain Monte Carlo.” I expect that part or all of this influential article was included in some published paper, but I only know it as a technical report–which at the time of this writing has been cited an impressive 78 times! This made me wonder: what are the most influential contributions to statistics that were never published (not counting posthumous publication or decades-later reprints in compilation volumes). Here’s all that I can think of: - Thomas Bayes’s original article, published only in 1763, two years after his death. - John Tukey’s legendary manuscript on multiple comparisons from the 1950s. I actually think Tukey’s work on multiple comparisons was horribly illogical stuff, very clever but also bad bad bad, and I’m very happy that he moved on to other things. But I can’t deny that his unpublished multiple compa
3 0.16752324 109 andrew gelman stats-2010-06-25-Classics of statistics
Introduction: Christian Robert is planning a graduate seminar in which students read 15 classic articles of statistics. (See here for more details and a slightly different list.) Actually, he just writes “classics,” but based on his list, I assume he only wants articles, not books. If he wanted to include classic books, I’d nominate the following, just for starters: - Fisher’s Statistical Methods for Research Workers - Snedecor and Cochran’s Statistical Methods - Kish’s Survey Sampling - Box, Hunter, and Hunter’s Statistics for Experimenters - Tukey’s Exploratory Data Analysis - Cleveland’s The Elements of Graphing Data - Mosteller and Wallace’s book on the Federalist Papers. Probably Cox and Hinkley, too. That’s a book that I don’t think has aged well, but it seems to have had a big influence. I think there’s a lot more good and accessible material in these classic books than in the equivalent volume of classic articles. Journal articles can be difficult to read and are typicall
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Introduction: I’m postponing today’s scheduled post (“Empirical implications of Empirical Implications of Theoretical Models”) to continue the lively discussion from yesterday, What if I were to stop publishing in journals? . An example: my papers with Basbøll Thomas Basbøll and I got into a long discussion on our blogs about business school professor Karl Weick and other cases of plagiarism copying text without attribution. We felt it useful to take our ideas to the next level and write them up as a manuscript, which ended up being logical to split into two papers. At that point I put some effort into getting these papers published, which I eventually did: To throw away data: Plagiarism as a statistical crime went into American Scientist and When do stories work? Evidence and illustration in the social sciences will appear in Sociological Methods and Research. The second paper, in particular, took some effort to place; I got some advice from colleagues in sociology as to where
5 0.15575103 1928 andrew gelman stats-2013-07-06-How to think about papers published in low-grade journals?
Introduction: We’ve had lots of lively discussions of fatally-flawed papers that have been published in top, top journals such as the American Economic Review or the Journal of Personality and Social Psychology or the American Sociological Review or the tabloids . And we also know about mistakes that make their way into mid-ranking outlets such as the Journal of Theoretical Biology. But what about results that appear in the lower tier of legitimate journals? I was thinking about this after reading a post by Dan Kahan slamming a paper that recently appeared in PLOS-One. I won’t discuss the paper itself here because that’s not my point. Rather, I had some thoughts regarding Kahan’s annoyance that a paper with fatal errors was published at all. I commented as follows: Read between the lines. The paper originally was released in 2009 and was published in 2013 in PLOS-One, which is one step above appearing on Arxiv. PLOS-One publishes some good things (so does Arxiv) but it’s the place
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Introduction: Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. I would be really curious to know your list too? Scarily enough I can’t think of any truly influential papers from that decade. I suppose this means I’m getting old! P.S. I did once make a list of the top 5 unpublished papers in statistics .
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Introduction: We’ve had lots of lively discussions of fatally-flawed papers that have been published in top, top journals such as the American Economic Review or the Journal of Personality and Social Psychology or the American Sociological Review or the tabloids . And we also know about mistakes that make their way into mid-ranking outlets such as the Journal of Theoretical Biology. But what about results that appear in the lower tier of legitimate journals? I was thinking about this after reading a post by Dan Kahan slamming a paper that recently appeared in PLOS-One. I won’t discuss the paper itself here because that’s not my point. Rather, I had some thoughts regarding Kahan’s annoyance that a paper with fatal errors was published at all. I commented as follows: Read between the lines. The paper originally was released in 2009 and was published in 2013 in PLOS-One, which is one step above appearing on Arxiv. PLOS-One publishes some good things (so does Arxiv) but it’s the place
3 0.76101601 1321 andrew gelman stats-2012-05-15-A statistical research project: Weeding out the fraudulent citations
Introduction: John Mashey points me to a blog post by Phil Davis on “the emergence of a citation cartel.” Davis tells the story: Cell Transplantation is a medical journal published by the Cognizant Communication Corporation of Putnam Valley, New York. In recent years, its impact factor has been growing rapidly. In 2006, it was 3.482 [I think he means "3.5"---ed.]. In 2010, it had almost doubled to 6.204. When you look at which journals cite Cell Transplantation, two journals stand out noticeably: the Medical Science Monitor, and The Scientific World Journal. According to the JCR, neither of these journals cited Cell Transplantation until 2010. Then, in 2010, a review article was published in the Medical Science Monitor citing 490 articles, 445 of which were to papers published in Cell Transplantation. All 445 citations pointed to papers published in 2008 or 2009 — the citation window from which the journal’s 2010 impact factor was derived. Of the remaining 45 citations, 44 cited the Me
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Introduction: I’ve whined before in this space that some of my most important, innovative, and influential papers are really hard to get published. I’ll go through endless hassle with a journal or sometimes several journals until I find some place willing to publish. It’s just irritating. I was thinking about this recently because a colleague and I just finished a paper that I love love love. But I can’t figure out where to submit it. This is a paper for which I would prefer the so-called reverse-journal-submission approach. Instead of sending the paper to journal after journal after journal, waiting years until an acceptance (recall that, unless you’re Bruno Frey, you’re not allowed to submit the same paper to multiple journals simultaneously), you post the paper on a public site, and then journals compete to see who gets to publish it. I think that system would work well with a paper like this which is offbeat but has a nontrivial chance of becoming highly influential. P.S. Just to clar
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Introduction: I’m postponing today’s scheduled post (“Empirical implications of Empirical Implications of Theoretical Models”) to continue the lively discussion from yesterday, What if I were to stop publishing in journals? . An example: my papers with Basbøll Thomas Basbøll and I got into a long discussion on our blogs about business school professor Karl Weick and other cases of plagiarism copying text without attribution. We felt it useful to take our ideas to the next level and write them up as a manuscript, which ended up being logical to split into two papers. At that point I put some effort into getting these papers published, which I eventually did: To throw away data: Plagiarism as a statistical crime went into American Scientist and When do stories work? Evidence and illustration in the social sciences will appear in Sociological Methods and Research. The second paper, in particular, took some effort to place; I got some advice from colleagues in sociology as to where
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Introduction: Jeff Leek writes: I just wrote this post about what the 5 most influential papers in statistics from 2000-2010. I would be really curious to know your list too? Scarily enough I can’t think of any truly influential papers from that decade. I suppose this means I’m getting old! P.S. I did once make a list of the top 5 unpublished papers in statistics .
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Introduction: Aleks pointed me to this interesting article by Sarah Slobin. I don’t have any good way of summarizing it, so you’ll just have to follow the link and read it.
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Introduction: I, like Steve Hsu , I too would love to read a definitive biography of John von Neumann (or, as we’d say in the U.S., “John Neumann”). I’ve read little things about him in various places such as Stanislaw Ulam’s classic autobiography, and two things I’ve repeatedly noticed are: 1. Neumann comes off as a obnoxious, self-satisfied jerk. He just seems like the kind of guy I wouldn’t like in real life. 2. All these great men seem to really have loved the guy. It’s hard for me to reconcile two impressions above. Of course, lots of people have a good side and a bad side, but what’s striking here is that my impressions of Neumann’s bad side come from the very stories that his friends use to demonstrate how lovable he was! So, yes, I’d like to see the biography–but only if it could resolve this paradox. Also, I don’t know how relevant this is, but Neumann shares one thing with the more-lovable Ulam and the less-lovable Mandelbrot: all had Jewish backgrounds but didn’t seem to
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Introduction: Charlie Williams writes: As I get interested in Bayesian approaches to statistics, I have one question I wondered if you would find interesting to address at some point on the blog. What does Bayesian work look like in action across a field? From experience, I have some feeling for how ongoing debates evolve (or not) with subsequent studies in response to earlier findings. I wonder if you know how this happens in practice when multiple researchers are using Bayesian approaches. How much are previous findings built into priors? How much advance comes from model improvement? And in a social science field where self-selection and self-interest play a role, how are improved “treatment” effects incorporated and evaluated? I thought you might know of a field where actual back and forth has been carried out mostly in the context of Bayesian analysis or inference, and I thought it would be interesting to take a look at an example as I think about my own field. My reply: I’ve seen Ba
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Introduction: I saw the trailer for the new Mr. Peabody movie and it looked terrible. They used that weird animation where everything looks round, also the voice had none of the intonations of the “real” Peabody (for some reason, the trailer had the original English voices, maybe they didn’t get their act together to make a dubbed trailer in time for the release here), also the scenes looked pretty stupid. I went back home and checked out Peabody on wikipedia and it turns out that they made 91 episodes! I had no idea. Anyway, here’s my real question: Why bother making a Mr. Peabody movie if you’re not going to do it well? I understand that lots of moviemakers are hacks and there will always be a huge audience for crap in any case, so I’m certainly not demanding that all movies be “good” (in whatever sense that means, from my perceptions). But there are lots and lots of opportunities to make crap movies, there are a million toys and video games and comic book characters and fairy tales and br
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