andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2320 knowledge-graph by maker-knowledge-mining
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Introduction: Can we make better graphs of global temperature history? Priors I don’t believe Cause he thinks he’s so-phisticated Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems What property is important in a risk prediction model? Discrimination or calibration? “What should you talk about?” Science tells us that fast food lovers are more likely to marry other fast food lovers Personally, I’d rather go with Teragram How much can we learn about individual-level causal claims from state-level correlations? Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Models with constraints Forum in Ecology on p-values and model selection Never back down: The culture of poverty and the culture of journalism M
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1 Can we make better graphs of global temperature history? [sent-1, score-0.168]
2 ” Science tells us that fast food lovers are more likely to marry other fast food lovers Personally, I’d rather go with Teragram How much can we learn about individual-level causal claims from state-level correlations? [sent-5, score-1.321]
3 Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? [sent-7, score-0.483]
4 Models with constraints Forum in Ecology on p-values and model selection Never back down: The culture of poverty and the culture of journalism My short career as a Freud expert “P. [sent-8, score-0.7]
5 An interesting mosaic of a data programming course Why I decided not to be a physicist Open-source tools for running online field experiments I was wrong . [sent-12, score-0.384]
6 Just wondering When you believe in things that you don’t understand I posted this as a comment on a sociology blog The role of technocratic thinking in economics and statistics This’ll take us to the end of May. [sent-15, score-0.31]
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same-blog 1 0.99999988 2320 andrew gelman stats-2014-05-05-On deck this month
Introduction: Can we make better graphs of global temperature history? Priors I don’t believe Cause he thinks he’s so-phisticated Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems What property is important in a risk prediction model? Discrimination or calibration? “What should you talk about?” Science tells us that fast food lovers are more likely to marry other fast food lovers Personally, I’d rather go with Teragram How much can we learn about individual-level causal claims from state-level correlations? Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Models with constraints Forum in Ecology on p-values and model selection Never back down: The culture of poverty and the culture of journalism M
2 0.4966096 2339 andrew gelman stats-2014-05-19-On deck this week
Introduction: Mon: My short career as a Freud expert Tues: “P.S. Is anyone working on hierarchical survival models?” Wed: Skepticism about a published claim regarding income inequality and happiness Thurs: Big Data needs Big Model Fri: Did Neyman really say of Fisher’s work, “It’s easy to get the right answer if you never define what the question is,” and did Fisher really describe Neyman as “a theorem-proving poseur who wouldn’t recognized real data if it bit him in the ass” Sat: An interesting mosaic of a data programming course Sun: Why I decided not to be a physicist
3 0.45056894 2331 andrew gelman stats-2014-05-12-On deck this week
Introduction: Mon: “The results (not shown) . . .” Tues: Personally, I’d rather go with Teragram Wed: How much can we learn about individual-level causal claims from state-level correlations? Thurs: Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Fri: Models with constraints Sat: Forum in Ecology on p-values and model selection Sun: Never back down: The culture of poverty and the culture of journalism
4 0.3834399 2321 andrew gelman stats-2014-05-05-On deck this week
Introduction: Mon: Can we make better graphs of global temperature history? Tues: Priors I don’t believe Wed: Cause he thinks he’s so-phisticated Thurs: Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Fri: Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems Sat: What property is important in a risk prediction model? Discrimination or calibration? Sun: “What should you talk about?” Plus whatever the co-bloggers want to throw in. Right now I’m super-excited about wedge sampling but I’ll let you know more about that once the paper is done.
5 0.26527539 2265 andrew gelman stats-2014-03-24-On deck this week
Introduction: OK, I’ve given up on theme weeks . I have enough saved-up material to do it, and it wouldn’t be too much trouble to group the scheduled posts into themes, but there doesn’t really seem to be a point. I say this because, having looked at the comment threads from the past few weeks, the comments seem pretty much tied to individual posts in any case. So I think I’ll go back to the old system where each post stands alone. Just for fun I thought I’d run a week’s worth of old posts, just some things I came across when searching for various things. Of course I could just post the links right here but instead I’ll repost with my comments on how things have changed in the intervening years. Mon : Empirical implications of Empirical Implications of Theoretical Models Tues : A statistical graphics course and statistical graphics advice Wed : What property is important in a risk prediction model? Discrimination or calibration? Thurs : Beyond the Valley of the Trolls Fri :
6 0.24881706 2264 andrew gelman stats-2014-03-24-On deck this month
8 0.21654193 1869 andrew gelman stats-2013-05-24-In which I side with Neyman over Fisher
9 0.14362256 1880 andrew gelman stats-2013-06-02-Flame bait
10 0.12027317 1999 andrew gelman stats-2013-08-27-Bayesian model averaging or fitting a larger model
11 0.11759675 2338 andrew gelman stats-2014-05-19-My short career as a Freud expert
12 0.10844067 754 andrew gelman stats-2011-06-09-Difficulties with Bayesian model averaging
13 0.10671534 2328 andrew gelman stats-2014-05-10-What property is important in a risk prediction model? Discrimination or calibration?
14 0.10624135 1414 andrew gelman stats-2012-07-12-Steven Pinker’s unconvincing debunking of group selection
15 0.10357946 98 andrew gelman stats-2010-06-19-Further thoughts on happiness and life satisfaction research
16 0.10236641 717 andrew gelman stats-2011-05-17-Statistics plagiarism scandal
17 0.10014433 391 andrew gelman stats-2010-11-03-Some thoughts on election forecasting
18 0.098676696 1369 andrew gelman stats-2012-06-06-Your conclusion is only as good as your data
19 0.096678331 1392 andrew gelman stats-2012-06-26-Occam
20 0.092200242 1633 andrew gelman stats-2012-12-21-Kahan on Pinker on politics
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same-blog 1 0.92943525 2320 andrew gelman stats-2014-05-05-On deck this month
Introduction: Can we make better graphs of global temperature history? Priors I don’t believe Cause he thinks he’s so-phisticated Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems What property is important in a risk prediction model? Discrimination or calibration? “What should you talk about?” Science tells us that fast food lovers are more likely to marry other fast food lovers Personally, I’d rather go with Teragram How much can we learn about individual-level causal claims from state-level correlations? Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Models with constraints Forum in Ecology on p-values and model selection Never back down: The culture of poverty and the culture of journalism M
2 0.8570956 2331 andrew gelman stats-2014-05-12-On deck this week
Introduction: Mon: “The results (not shown) . . .” Tues: Personally, I’d rather go with Teragram Wed: How much can we learn about individual-level causal claims from state-level correlations? Thurs: Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Fri: Models with constraints Sat: Forum in Ecology on p-values and model selection Sun: Never back down: The culture of poverty and the culture of journalism
3 0.85535747 2339 andrew gelman stats-2014-05-19-On deck this week
Introduction: Mon: My short career as a Freud expert Tues: “P.S. Is anyone working on hierarchical survival models?” Wed: Skepticism about a published claim regarding income inequality and happiness Thurs: Big Data needs Big Model Fri: Did Neyman really say of Fisher’s work, “It’s easy to get the right answer if you never define what the question is,” and did Fisher really describe Neyman as “a theorem-proving poseur who wouldn’t recognized real data if it bit him in the ass” Sat: An interesting mosaic of a data programming course Sun: Why I decided not to be a physicist
4 0.84508115 2321 andrew gelman stats-2014-05-05-On deck this week
Introduction: Mon: Can we make better graphs of global temperature history? Tues: Priors I don’t believe Wed: Cause he thinks he’s so-phisticated Thurs: Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Fri: Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems Sat: What property is important in a risk prediction model? Discrimination or calibration? Sun: “What should you talk about?” Plus whatever the co-bloggers want to throw in. Right now I’m super-excited about wedge sampling but I’ll let you know more about that once the paper is done.
5 0.73815143 2265 andrew gelman stats-2014-03-24-On deck this week
Introduction: OK, I’ve given up on theme weeks . I have enough saved-up material to do it, and it wouldn’t be too much trouble to group the scheduled posts into themes, but there doesn’t really seem to be a point. I say this because, having looked at the comment threads from the past few weeks, the comments seem pretty much tied to individual posts in any case. So I think I’ll go back to the old system where each post stands alone. Just for fun I thought I’d run a week’s worth of old posts, just some things I came across when searching for various things. Of course I could just post the links right here but instead I’ll repost with my comments on how things have changed in the intervening years. Mon : Empirical implications of Empirical Implications of Theoretical Models Tues : A statistical graphics course and statistical graphics advice Wed : What property is important in a risk prediction model? Discrimination or calibration? Thurs : Beyond the Valley of the Trolls Fri :
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8 0.68595171 2240 andrew gelman stats-2014-03-10-On deck this week: Things people sent me
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14 0.64425117 2253 andrew gelman stats-2014-03-17-On deck this week: Revisitings
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20 0.56233233 976 andrew gelman stats-2011-10-27-Geophysicist Discovers Modeling Error (in Economics)
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same-blog 1 0.97987509 2320 andrew gelman stats-2014-05-05-On deck this month
Introduction: Can we make better graphs of global temperature history? Priors I don’t believe Cause he thinks he’s so-phisticated Discussion with Steven Pinker on research that is attached to data that are so noisy as to be essentially uninformative Combining forecasts: Evidence on the relative accuracy of the simple average and Bayesian model averaging for predicting social science problems What property is important in a risk prediction model? Discrimination or calibration? “What should you talk about?” Science tells us that fast food lovers are more likely to marry other fast food lovers Personally, I’d rather go with Teragram How much can we learn about individual-level causal claims from state-level correlations? Bill Easterly vs. Jeff Sachs: What percentage of the recipients didn’t use the free malaria bed nets in Zambia? Models with constraints Forum in Ecology on p-values and model selection Never back down: The culture of poverty and the culture of journalism M
Introduction: I came across this from Jeff Sachs: [Bill Easterly in his 2006 book] went on to write that “a study of a program to hand out free [malaria bed] nets in Zambia to people … found that 70 percent of the recipients didn’t use the nets.” Yet this particular study, which was conducted by the American Red Cross and CORE, actually showed the program was a success, with high rates of net adoption. Sachs provides a link to this 2004 study . I followed the link and took a quick look at the study, and indeed in the intro it says, “Household ITN coverage increased from 28.9 percent (pre-campaign) to 85 percent (with a greater than 80 percent coverage across all wealth quintiles). . . . At six months post-campaign . . . and 60 percent of the pregnant women and children under 5 years old were reported to have slept under the net the previous night.” 60% of 85% is far from ideal but it’s a lot higher than “70 percent of the recipients didn’t use the nets.” But I am no expert in this area
3 0.95979393 550 andrew gelman stats-2011-02-02-An IV won’t save your life if the line is tangled
Introduction: Alex Tabarrok quotes Randall Morck and Bernard Yeung on difficulties with instrumental variables. This reminded me of some related things I’ve written. In the official story the causal question comes first and then the clever researcher comes up with an IV. I suspect that often it’s the other way around: you find a natural experiment and look at the consequences that flow from it. And maybe that’s not such a bad thing. See section 4 of this article . More generally, I think economists and political scientists are currently a bit overinvested in identification strategies. I agree with Heckman’s point (as I understand it) that ultimately we should be building models that work for us rather than always thinking we can get causal inference on the cheap, as it were, by some trick or another. (This is a point I briefly discuss in a couple places here and also in my recent paper for the causality volume that Don Green etc are involved with.) I recently had this discussion wi
4 0.95907414 1079 andrew gelman stats-2011-12-23-Surveys show Americans are populist class warriors, except when they aren’t
Introduction: From my New York Times blog today, here’s an example of how contemporaneous poll results can be given exactly opposite interpretations. Recently in the New Republic, William Galston shared some recent findings from Gallup: Respondents were asked to categorize three economic objectives as extremely important, very important, somewhat important, or not important. Here’s what they said: Extremely/very important Somewhat/not important Grow and expand the economy 82 18 Increase equality of opportunity for people to get ahead 70 30 Reduce the income and wealth gap between the rich and the poor 46 54 When Gallup asked a sample of Americans in 1998 whether the gap between the rich and the poor was a problem that needed t
5 0.95708066 624 andrew gelman stats-2011-03-22-A question about the economic benefits of universities
Introduction: Ed Glaeser writes : The late Senator Daniel Patrick Moynihan of New York is often credited with saying that the way to create a great city is to “create a great university and wait 200 years,” and the body of evidence on the role that universities play in generating urban growth continues to grow. I’ve always thought this too, that it’s too bad that, given the total cost, a lot more cities would’ve benefited, over the years, by maintaining great universities rather than building expensive freeways, RenCens, and so forth. But Joseph Delaney argues the opposite , considering the case of New Haven, home of what is arguably the second-best university in the country (I assume Glaeser would agree with me on this one): According to wikipedia, the poverty rate in New Haven is 24%, which compares unfavorably with the rest of the United States where it is 14%. The poverty rate in New Haven, despite the presence of Yale, is nearly twice that of the United States as a whole. Now,
6 0.95678389 83 andrew gelman stats-2010-06-13-Silly Sas lays out old-fashioned statistical thinking
7 0.95613635 68 andrew gelman stats-2010-06-03-…pretty soon you’re talking real money.
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12 0.94979465 751 andrew gelman stats-2011-06-08-Another Wegman plagiarism
13 0.94903982 1453 andrew gelman stats-2012-08-10-Quotes from me!
14 0.94851696 2307 andrew gelman stats-2014-04-27-Big Data…Big Deal? Maybe, if Used with Caution.
15 0.94804001 368 andrew gelman stats-2010-10-25-Is instrumental variables analysis particularly susceptible to Type M errors?
16 0.94610667 2286 andrew gelman stats-2014-04-08-Understanding Simpson’s paradox using a graph
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18 0.9449625 1105 andrew gelman stats-2012-01-08-Econ debate about prices at a fancy restaurant
19 0.94457936 629 andrew gelman stats-2011-03-26-Is it plausible that 1% of people pick a career based on their first name?
20 0.94429791 257 andrew gelman stats-2010-09-04-Question about standard range for social science correlations