andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-80 knowledge-graph by maker-knowledge-mining
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Introduction: George Leckie points to this free online course from the Centre for Multilevel Modelling (approx 600 pages of materials covering theory and implementation in MLwiN and Stata).
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same-blog 1 1.0 80 andrew gelman stats-2010-06-11-Free online course in multilevel modeling
Introduction: George Leckie points to this free online course from the Centre for Multilevel Modelling (approx 600 pages of materials covering theory and implementation in MLwiN and Stata).
2 0.36201441 857 andrew gelman stats-2011-08-17-Bayes pays
Introduction: George Leckie writes: The Centre for Multilevel Modelling at the University of Bristol is seeking to appoint an applied statistician to work on a new ESRC-funded project, Longitudinal Effects, Multilevel Modelling and Applications (LEMMA 3). LEMMA 3 is one of six Nodes of the National Centre for Research Methods (NCRM). The LEMMA 3 Node will focus on methods for the analysis of longitudinal data. The appointment, at Research Assistant or Research Associate level, will be for 2.5 years with likelihood of extension to the end of September 2014. For further details, including information on how to apply online, please go to http://www.bris.ac.uk/boris/jobs/feeds/ads?ID=100571 By “modelling,” I think he means “modeling.” And by “centre,” I think he means “center.” But I think you get the basic idea. It looks like a great place to do research.
3 0.33032823 202 andrew gelman stats-2010-08-12-Job openings in multilevel modeling in Bristol, England
Introduction: George Leckie writes: The Centre for Multilevel Modelling is seeking to appoint two social statisticians or social scientists with advanced quantitative skills for two ESRC-funded research projects : 1. Research Assistant in Social Statistics, 1 year from 1 October 2010 2. Research Assistant/Associate in Social Statistics, 34 months from 1 October 2010.
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Introduction: Is there an implementation of bayesglm in Stata? (That is, approximate maximum penalized likelihood estimation with specified normal or t prior distributions on the coefficients.)
Introduction: You know that expression, “Not from the Onion”? How did we say that, all those years before the Onion existed? I was thinking about this after encountering (amidst a Google search for something else) this article on a website called “College News”: DANVILLE, KY., March 8, 2007–Two Centre College professors spent the past six years reading and analyzing 200 children’s books to discover a disturbing trend: gender bias still exists in much of modern children’s literature. Dr. David Anderson, professor of economics, and Dr. Mykol Hamilton, professor of psychology, have documented that gender bias is common today in many children’s books in their research published recently in Sex Roles: A Journal of Research titled “Gender Stereotyping and Under-Representation of Female Characters in 200 Popular Children’s Picture Books: A 21st Century Update.” . . . “Centre College,” huh? That’s where Area Man is studying, right? According to the materials on its website, Centre College is
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same-blog 1 0.98367155 80 andrew gelman stats-2010-06-11-Free online course in multilevel modeling
Introduction: George Leckie points to this free online course from the Centre for Multilevel Modelling (approx 600 pages of materials covering theory and implementation in MLwiN and Stata).
2 0.69597834 857 andrew gelman stats-2011-08-17-Bayes pays
Introduction: George Leckie writes: The Centre for Multilevel Modelling at the University of Bristol is seeking to appoint an applied statistician to work on a new ESRC-funded project, Longitudinal Effects, Multilevel Modelling and Applications (LEMMA 3). LEMMA 3 is one of six Nodes of the National Centre for Research Methods (NCRM). The LEMMA 3 Node will focus on methods for the analysis of longitudinal data. The appointment, at Research Assistant or Research Associate level, will be for 2.5 years with likelihood of extension to the end of September 2014. For further details, including information on how to apply online, please go to http://www.bris.ac.uk/boris/jobs/feeds/ads?ID=100571 By “modelling,” I think he means “modeling.” And by “centre,” I think he means “center.” But I think you get the basic idea. It looks like a great place to do research.
3 0.57019073 202 andrew gelman stats-2010-08-12-Job openings in multilevel modeling in Bristol, England
Introduction: George Leckie writes: The Centre for Multilevel Modelling is seeking to appoint two social statisticians or social scientists with advanced quantitative skills for two ESRC-funded research projects : 1. Research Assistant in Social Statistics, 1 year from 1 October 2010 2. Research Assistant/Associate in Social Statistics, 34 months from 1 October 2010.
4 0.56141305 1220 andrew gelman stats-2012-03-19-Sorry, no ARM solutions
Introduction: Daniel Gerlanc asks: I’ve been reading your Regression and Multilevel Modeling book. Do you have a set of example solutions for the problems in the book? Henning Piezunka, Adam Lynton, and others have asked the same question. My universal response: I’m glad you like our book. Unfortunately, we have no solution sets. I made a bunch of solutions for my earlier book but it was so much work that I decided not to do it a second time!
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Introduction: Yi-Chun Ou writes: I am using a multilevel model with three levels. I read that you wrote a book about multilevel models, and wonder if you can solve the following question. The data structure is like this: Level one: customer (8444 customers) Level two: companys (90 companies) Level three: industry (17 industries) I use 6 level-three variables (i.e. industry characteristics) to explain the variance of the level-one effect across industries. The question here is whether there is an over-fitting problem since there are only 17 industries. I understand that this must be a problem for non-multilevel models, but is it also a problem for multilevel models? My reply: Yes, this could be a problem. I’d suggest combining some of your variables into a common score, or using only some of the variables, or using strong priors to control the inferences. This is an interesting and important area of statistics research, to do this sort of thing systematically. There’s lots o
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same-blog 1 0.93817616 80 andrew gelman stats-2010-06-11-Free online course in multilevel modeling
Introduction: George Leckie points to this free online course from the Centre for Multilevel Modelling (approx 600 pages of materials covering theory and implementation in MLwiN and Stata).
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Introduction: Today I was reminded of a riddle from junior high: Q: What do you get when you cross an elephant with peanut butter? A: Peanut butter that never forgets, or an elephant that sticks to the roof of your mouth. The occasion was a link from Tyler Cowen to a new book by Garry Kasparov and . . . Peter Thiel. Kasparov we all know about. I still remember how he pulled out a victory in the last game of his tournament with Karpov. Just amazing: he had to win the game, a draw would not be enough. Both players knew that Kasparov had to win. And he did it. A feat as impressive as Kirk Gibson’s off-the-bench game-winning home run in the 1987 Series. Peter Theil is a more obscure figure. He’s been featured a couple of times on this blog and comes across as your typical overconfident rich dude. It’s an odd combination, sort of like what you might get if Rickey Henderson and Peter Angelos were to write a book about how to reform baseball. Cowen writes, “How can I not pre-orde
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Introduction: Sciencedaily has posted an article titled Apes Unwilling to Gamble When Odds Are Uncertain : The apes readily distinguished between the different probabilities of winning: they gambled a lot when there was a 100 percent chance, less when there was a 50 percent chance, and only rarely when there was no chance In some trials, however, the experimenter didn’t remove a lid from the bowl, so the apes couldn’t assess the likelihood of winning a banana The odds from the covered bowl were identical to those from the risky option: a 50 percent chance of getting the much sought-after banana. But apes of both species were less likely to choose this ambiguous option. Like humans, they showed “ambiguity aversion” — preferring to gamble more when they knew the odds than when they didn’t. Given some of the other differences between chimps and bonobos, Hare and Rosati had expected to find the bonobos to be more averse to ambiguity, but that didn’t turn out to be the case. Thanks to Sta
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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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Introduction: A University of Delaware press release reports : This month, the Journal of Quantitative Analysis in Sports will feature the article “An Estimate of How Hitting, Pitching, Fielding, and Base-stealing Impact Team Winning Percentages in Baseball.” In it, University of Delaware Prof. Charles Pavitt of the Department of Communication defines the perfect “formula” for Major League Baseball (MLB) teams to use to build the ultimate winning team. Pavitt found hitting accounts for more than 45 percent of teams’ winning records, fielding for 25 percent and pitching for 25 percent. And that the impact of stolen bases is greatly overestimated. He crunched hitting, pitching, fielding and base-stealing records for every MLB team over a 48-year period from 1951-1998 with a method no other researcher has used in this area. In statistical parlance, he used a conceptual decomposition of offense and defense into its component parts and then analyzed recombinations of the parts in intuitively mea
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