andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2265 knowledge-graph by maker-knowledge-mining
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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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1 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. [sent-2, score-0.537]
2 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. [sent-3, score-0.688]
3 So I think I’ll go back to the old system where each post stands alone. [sent-4, score-0.33]
4 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. [sent-5, score-0.233]
5 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. [sent-6, score-0.739]
6 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? [sent-7, score-1.054]
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same-blog 1 1.0000001 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 :
2 0.34996921 2264 andrew gelman stats-2014-03-24-On deck this month
Introduction: Actually, more like the next month and a half . . . I just have this long backlog so I thought I might as well share it with you: Empirical implications of Empirical Implications of Theoretical Models A statistical graphics course and statistical graphics advice What property is important in a risk prediction model? Discrimination or calibration? Beyond the Valley of the Trolls Science tells us that fast food lovers are more likely to marry other fast food lovers References (with code) for Bayesian hierarchical (multilevel) modeling and structural equation modeling Adjudicating between alternative interpretations of a statistical interaction? The most-cited statistics papers ever American Psychological Society announces a new journal Am I too negative? As the boldest experiment in journalism history, you admit you made a mistake Personally, I’d rather go with Teragram Bizarre academic spam An old discussion of food deserts Skepticism about a published cl
3 0.33517563 2253 andrew gelman stats-2014-03-17-On deck this week: Revisitings
Introduction: 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 : In the best alternative histories, the real world is what’s ultimately real (from 2005) Tues : Comments on an anti-Bayesian (from 2006) Wed : How Americans vote (from 2012) Thurs : The candy weighing demonstration, or, the unwisdom of crowds (from 2008) Fri : Random matrices in the news (from 2010) Sat : Picking pennies in front of a steamroller: A parable comes to life (from 2011) Sun : Greg Mankiw’s utility function (from 2010)
4 0.29500777 2240 andrew gelman stats-2014-03-10-On deck this week: Things people sent me
Introduction: Mon: Preregistration: what’s in it for you? Tues: What if I were to stop publishing in journals? Wed: Empirical implications of Empirical Implications of Theoretical Models Thurs: An Economist’s Guide to Visualizing Data Fri: The maximal information coefficient Sat: Problematic interpretations of confidence intervals Sun: The more you look, the more you find
5 0.26527539 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
6 0.24522962 2321 andrew gelman stats-2014-05-05-On deck this week
7 0.18193087 2276 andrew gelman stats-2014-03-31-On deck this week
8 0.16972248 2206 andrew gelman stats-2014-02-10-On deck this week
9 0.16922218 2290 andrew gelman stats-2014-04-14-On deck this week
10 0.16076328 2366 andrew gelman stats-2014-06-09-On deck this week
11 0.15487514 2348 andrew gelman stats-2014-05-26-On deck this week
12 0.1531968 2339 andrew gelman stats-2014-05-19-On deck this week
13 0.15188611 2232 andrew gelman stats-2014-03-03-What is the appropriate time scale for blogging—the day or the week?
14 0.14114447 2331 andrew gelman stats-2014-05-12-On deck this week
15 0.1389278 2285 andrew gelman stats-2014-04-07-On deck this week
17 0.13358276 826 andrew gelman stats-2011-07-27-The Statistics Forum!
18 0.12363051 2298 andrew gelman stats-2014-04-21-On deck this week
19 0.12278438 2356 andrew gelman stats-2014-06-02-On deck this week
20 0.12043569 1964 andrew gelman stats-2013-08-01-Non-topical blogging
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same-blog 1 0.95961225 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 :
2 0.88776213 2253 andrew gelman stats-2014-03-17-On deck this week: Revisitings
Introduction: 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 : In the best alternative histories, the real world is what’s ultimately real (from 2005) Tues : Comments on an anti-Bayesian (from 2006) Wed : How Americans vote (from 2012) Thurs : The candy weighing demonstration, or, the unwisdom of crowds (from 2008) Fri : Random matrices in the news (from 2010) Sat : Picking pennies in front of a steamroller: A parable comes to life (from 2011) Sun : Greg Mankiw’s utility function (from 2010)
3 0.85600817 2298 andrew gelman stats-2014-04-21-On deck this week
Introduction: Mon : Ticket to Baaaath Tues : Ticket to Baaaaarf Wed : Thinking of doing a list experiment? Here’s a list of reasons why you should think again Thurs : An open site for researchers to post and share papers Fri : Questions about “Too Good to Be True” Sat : Sleazy sock puppet can’t stop spamming our discussion of compressed sensing and promoting the work of Xiteng Liu Sun : White stripes and dead armadillos
4 0.82894123 2276 andrew gelman stats-2014-03-31-On deck this week
Introduction: Mon : The most-cited statistics papers ever Tues : American Psychological Society announces a new journal Wed : Am I too negative? Thurs : As the boldest experiment in journalism history, you admit you made a mistake Fri : The Notorious N.H.S.T. presents: Mo P-values Mo Problems Sat : Bizarre academic spam Sun : An old discussion of food deserts
5 0.80760217 2206 andrew gelman stats-2014-02-10-On deck this week
Introduction: This blog has roughly a month’s worth of items waiting to be posted. I post about once a day, sometimes rescheduling posts to make room for something topical. Anyway, it struck me that I know what’s coming up, but you don’t. So, here’s what we have for you during the next few days: Mon: More on US health care overkill Tues: My talks in Bristol this Wed and London this Thurs Wed: How to think about “identifiability” in Bayesian inference? Thurs: Stopping rules and Bayesian analysis Fri: The popularity of certain baby names is falling off the clifffffffffffff Plus anything our cobloggers might choose to post during these days. And, if Woody Allen or Ed Wegman or anyone else newsworthy asks us to publish an op-ed for them, we’ll consider it. Enjoy.
6 0.80307972 2348 andrew gelman stats-2014-05-26-On deck this week
7 0.80307561 2285 andrew gelman stats-2014-04-07-On deck this week
8 0.79739666 2240 andrew gelman stats-2014-03-10-On deck this week: Things people sent me
9 0.79612088 2310 andrew gelman stats-2014-04-28-On deck this week
10 0.79230231 2264 andrew gelman stats-2014-03-24-On deck this month
11 0.78768528 2290 andrew gelman stats-2014-04-14-On deck this week
12 0.78166777 2321 andrew gelman stats-2014-05-05-On deck this week
13 0.76174951 2366 andrew gelman stats-2014-06-09-On deck this week
14 0.75660318 2331 andrew gelman stats-2014-05-12-On deck this week
15 0.74944252 2339 andrew gelman stats-2014-05-19-On deck this week
16 0.73909289 2214 andrew gelman stats-2014-02-17-On deck this week
17 0.71159357 2356 andrew gelman stats-2014-06-02-On deck this week
18 0.70189315 2222 andrew gelman stats-2014-02-24-On deck this week
19 0.62873548 2320 andrew gelman stats-2014-05-05-On deck this month
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same-blog 1 0.9825772 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 :
2 0.96720159 35 andrew gelman stats-2010-05-16-Another update on the spam email study
Introduction: I think youall are probably getting sick of this by now so I’ll put it all below the fold. Akinola Modupe and Katherine Milkman responded to my email about their study : We want to clarify the reason we believe that the use of deception and a lack of informed consent were appropriate and ethical for this research study. In this project, we were studying how the timing of a decision affects discrimination based on race and/or gender. The emails all participants in our study received were identical except for a) the sender’s name (we used 20 names that pretesting revealed were strongly associated with being either Caucasian, Black, Indian, Chinese or Hispanic, as well as associated with being male or female) and b) whether the meeting requested was for today or for a week from today. Recipients were randomly selected and were randomly assigned to one of the race/gender/timing conditions. This study design will allow us to test for baseline levels of discrimination in acade
3 0.9667871 1369 andrew gelman stats-2012-06-06-Your conclusion is only as good as your data
Introduction: Jay Livingston points to an excellent rant from Peter Moskos, trashing a study about “food deserts” (which I kept reading as “food desserts”) in inner-city neighborhoods. Here’s Moskos: From the Times: There is no relationship between the type of food being sold in a neighborhood and obesity among its children and adolescents. Within a couple of miles of almost any urban neighborhood, “you can get basically any type of food,” said Roland Sturm of the RAND Corporation, lead author of one of the studies. “Maybe we should call it a food swamp rather than a desert,” he said. Sure thing, Sturm. But I suspect you wouldn’t think certain neighborhoods are swamped with good food if you actually got out of your office and went to one of the neighborhoods. After all, what are going to believe: A nice data set or your lying eyes? “Food outlet data … are classifıed using the North American Industry Classifıcation System (NAICS)” (p. 130). Assuming validity and reliability of NAICS
Introduction: Paul Alper writes: Unless I missed it, you haven’t commented on the recent article of Michael Bang Peterson [with Daniel Sznycer, Aaron Sell, Leda Cosmides, and John Tooby]. It seems to have been reviewed extensively in the lay press. A typical example is here . This review begins with “If you are physically strong, social science scholars believe they can predict whether or not you are more conservative than other men…Men’s upper-body strength predicts their political opinions on economic redistribution, they write, and they believe that the link may reflect psychological traits that evolved in response to our early ancestral environments and continue to influence behavior today. . . . they surveyed hundreds of people in America, Denmark and Argentina about bicep size, socioeconomic status, and support for economic redistribution.” Further, “Despite the fact that the United States, Denmark and Argentina have very different welfare systems, we still see that — at the psychol
5 0.96412122 1120 andrew gelman stats-2012-01-15-Fun fight over the Grover search algorithm
Introduction: Joshua Vogelstein points me to this blog entry by Robert Tucci, diplomatically titled “Unethical or Really Dumb (or both) Scientists from University of Adelaide ‘Rediscover’ My Version of Grover’s Algorithm”: The Chappell et al. paper has 24 references but does not refer to my paper, even though their paper and mine are eerily similar. Compare them yourself. With the excellent Google and ArXiv search engines, I [Tucci] would say there is zero probability that none of its five authors knew about my paper before they wrote theirs. Chappell responds in the comments: Your paper is timestamped 2010; however the results of our paper was initially presented at the Cairns CQIQC conference in July 2008. . . . The intention of our paper is not a research article. It is a tutorial paper. . . . We had not seen your paper before. Our paper is based on the standard Grover search, not a fixed point search. Hence, your paper did not come to our attention, as we were not concerned with
6 0.96307695 583 andrew gelman stats-2011-02-21-An interesting assignment for statistical graphics
7 0.96247327 1108 andrew gelman stats-2012-01-09-Blogging, polemical and otherwise
8 0.96199954 342 andrew gelman stats-2010-10-14-Trying to be precise about vagueness
9 0.96163046 2347 andrew gelman stats-2014-05-25-Why I decided not to be a physicist
10 0.96057135 2115 andrew gelman stats-2013-11-27-Three unblinded mice
11 0.95980078 1460 andrew gelman stats-2012-08-16-“Real data can be a pain”
12 0.95913625 1269 andrew gelman stats-2012-04-19-Believe your models (up to the point that you abandon them)
13 0.95883924 1588 andrew gelman stats-2012-11-23-No one knows what it’s like to be the bad man
14 0.95843565 773 andrew gelman stats-2011-06-18-Should we always be using the t and robit instead of the normal and logit?
15 0.95815653 1868 andrew gelman stats-2013-05-23-Validation of Software for Bayesian Models Using Posterior Quantiles
16 0.95803797 1611 andrew gelman stats-2012-12-07-Feedback on my Bayesian Data Analysis class at Columbia
18 0.95790023 10 andrew gelman stats-2010-04-29-Alternatives to regression for social science predictions
20 0.95779836 855 andrew gelman stats-2011-08-16-Infovis and statgraphics update update