andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2188 knowledge-graph by maker-knowledge-mining
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Introduction: This , sent in by Ben Bolker, is just tooooo funny. Click on the above image to see more clearly. In addition to the quote I used in the above title, there’s also this: +10.000 correlations/min Sooner than later, your future discovery will pop up. and this: The most relevant conclusions in your scientific paper are concealed under the experimental data but you simply cannot see them. All they need is to pipe in a Mechanical Turk request form on one end and a Psychological Science submission form on the other, and they’ll have the complete package!
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1 This , sent in by Ben Bolker, is just tooooo funny. [sent-1, score-0.124]
2 In addition to the quote I used in the above title, there’s also this: +10. [sent-3, score-0.408]
3 000 correlations/min Sooner than later, your future discovery will pop up. [sent-4, score-0.544]
4 and this: The most relevant conclusions in your scientific paper are concealed under the experimental data but you simply cannot see them. [sent-5, score-1.129]
5 All they need is to pipe in a Mechanical Turk request form on one end and a Psychological Science submission form on the other, and they’ll have the complete package! [sent-6, score-1.56]
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same-blog 1 1.0 2188 andrew gelman stats-2014-01-27-“Disappointed with your results? Boost your scientific paper”
Introduction: This , sent in by Ben Bolker, is just tooooo funny. Click on the above image to see more clearly. In addition to the quote I used in the above title, there’s also this: +10.000 correlations/min Sooner than later, your future discovery will pop up. and this: The most relevant conclusions in your scientific paper are concealed under the experimental data but you simply cannot see them. All they need is to pipe in a Mechanical Turk request form on one end and a Psychological Science submission form on the other, and they’ll have the complete package!
2 0.16642448 40 andrew gelman stats-2010-05-18-What visualization is best?
Introduction: Jeff Heer and Mike Bostock provided Mechanical Turk workers with a problem they had to answer using different types of charts. The lower error the workers got, the better the visualization. Here are some results from their paper Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design : They also looked at various settings, like density, aspect ratio, spacing, etc. Visualization has become empirical science, no longer just art.
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Introduction: Dan Kahan gives a bunch of reasons not to trust Mechanical Turk in psychology experiments, in particular when studying “hypotheses about cognition and political conflict over societal risks and other policy-relevant facts.”
4 0.13273621 1134 andrew gelman stats-2012-01-21-Lessons learned from a recent R package submission
Introduction: R has zillions of packages, and people are submitting new ones each day . The volunteers who keep R going are doing an incredibly useful service to the profession, and they’re busy . A colleague sends in some suugestions based on a recent experience with a package update: 1. Always use the R dev version to write a package. Not the current stable release. The R people use the R dev version to check your package anyway. If you don’t use the R dev version, there is chance that your package won’t pass the check. In my own experience, every time R has a major change, it tends to have new standards and find new errors in your package with these new standards. So better use the dev version to find out the potential errors in advance. 2. After submission, write an email to claim it. I used to submit the package to the CRAN without writing an email. This was standard operating procedure, but it has changed. Writing an email to claim about the submission is now a requir
5 0.11197244 1682 andrew gelman stats-2013-01-19-R package for Bayes factors
Introduction: Richard Morey writes: You and your blog readers may be interested to know that a we’ve released a major new version of the BayesFactor package to CRAN. The package computes Bayes factors for linear mixed models and regression models. Of course, I’m aware you don’t like point-null model comparisons, but the package does more than that; it also allows sampling from posterior distributions of the compared models, in much the same way that your arm package does with lmer objects. The sampling (both for the Bayes factors and posteriors) is quite fast, since the back end is written in C. Some basic examples using the package can be found here , and the CRAN page is here . Indeed I don’t like point-null model comparisons . . . but maybe this will be useful to some of you!
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Introduction: This , sent in by Ben Bolker, is just tooooo funny. Click on the above image to see more clearly. In addition to the quote I used in the above title, there’s also this: +10.000 correlations/min Sooner than later, your future discovery will pop up. and this: The most relevant conclusions in your scientific paper are concealed under the experimental data but you simply cannot see them. All they need is to pipe in a Mechanical Turk request form on one end and a Psychological Science submission form on the other, and they’ll have the complete package!
2 0.66644937 302 andrew gelman stats-2010-09-28-This is a link to a news article about a scientific paper
Introduction: Somebody I know sent me a link to this news article by Martin Robbins describing a potential scientific breakthrough. I express some skepticism but in a vague enough way that, in the unlikely event that the research claim turns out to be correct, there’s no paper trail showing that I was wrong. I have some comments on the graphs–the tables are horrible, no need to even discuss them!–and I’d prefer if the authors of the paper could display their data and model on a single graph. I realize that their results reached a standard level of statistical significance, but it’s hard for me to interpret their claims until I see their estimates on some sort of direct real-world scale. In any case, though, I’m sure these researchers are working hard, and I wish them the best of luck in their future efforts to replicate their findings. I’m sure they’ll have no problem replicating, whether or not their claims are actually true. That’s the way science works: Once you know what you’re looking
3 0.66431057 2289 andrew gelman stats-2014-04-11-“More research from the lunatic fringe”
Introduction: A linguist send me an email with the above title and a link to a paper, “The Effect of Language on Economic Behavior: Evidence from Savings Rates, Health Behaviors, and Retirement Assets,” by M. Keith Chen, which begins: Languages differ widely in the ways they encode time. I test the hypothesis that languages that grammatically associate the future and the present, foster future-oriented behavior. This prediction arises naturally when well-documented e§ects of language structure are merged with models of intertemporal choice. Empirically, I find that speakers of such languages: save more, retire with more wealth, smoke less, practice safer sex, and are less obese. This holds both across countries and within countries when comparing demographically similar native households. The evidence does not support the most obvious forms of common causation. I discuss implications for theories of intertemporal choice. I ran this by another linguist who confirmed the “lunatic fringe” comme
4 0.6576193 908 andrew gelman stats-2011-09-14-Type M errors in the lab
Introduction: Jeff points us to this news article by Asher Mullard: Bayer halts nearly two-thirds of its target-validation projects because in-house experimental findings fail to match up with published literature claims, finds a first-of-a-kind analysis on data irreproducibility. An unspoken industry rule alleges that at least 50% of published studies from academic laboratories cannot be repeated in an industrial setting, wrote venture capitalist Bruce Booth in a recent blog post. A first-of-a-kind analysis of Bayer’s internal efforts to validate ‘new drug target’ claims now not only supports this view but suggests that 50% may be an underestimate; the company’s in-house experimental data do not match literature claims in 65% of target-validation projects, leading to project discontinuation. . . . Khusru Asadullah, Head of Target Discovery at Bayer, and his colleagues looked back at 67 target-validation projects, covering the majority of Bayer’s work in oncology, women’s health and cardiov
5 0.65714765 1990 andrew gelman stats-2013-08-20-Job opening at an organization that promotes reproducible research!
Introduction: I was told about an organization called Reproducibility Initiative. They tell me they are trying to make what was described in our “50 shades of gray” post standard across all of science, particularly areas like cancer research. I don’t know anything else about them, but that sounds like a good start! Here’s the ad: Data Scientist: Science Exchange, Palo Alto, CA Science Exchange is an innovative start-up with a mission to improve the efficiency and quality of scientific research. This Data Science position is critical to our mission. Our ideal candidate has the ability to collect and normalize data from multiple sources. This information will be used to drive marketing and product decisions, as well as fuel many of the features of Science Exchange. Desired Skills & Experience Experience with text mining, entity extraction and natural language processing is essential Experience scripting with either Python or R Experience running complex statistical analyses on l
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same-blog 1 0.94441777 2188 andrew gelman stats-2014-01-27-“Disappointed with your results? Boost your scientific paper”
Introduction: This , sent in by Ben Bolker, is just tooooo funny. Click on the above image to see more clearly. In addition to the quote I used in the above title, there’s also this: +10.000 correlations/min Sooner than later, your future discovery will pop up. and this: The most relevant conclusions in your scientific paper are concealed under the experimental data but you simply cannot see them. All they need is to pipe in a Mechanical Turk request form on one end and a Psychological Science submission form on the other, and they’ll have the complete package!
2 0.94341433 1800 andrew gelman stats-2013-04-12-Too tired to mock
Introduction: Someone sent me an email with the subject line “A terrible infographic,” and it went on from there: “Given some of your recent writing on infovis, I thought you might get a kick out of this . . . I’m certainly sympathetic to their motivations, but some of these plots do not aid understanding… To pick on a few in particular, the first plot attached, cropped from the infographic, is a strange alternative to a bar plot. For the second attachment, I still don’t understand what they’ve plotted. . . .” I agree with everything he wrote, but this point I think I’m getting too exhausted to laugh at graphs unless there is an obvious political bias to point to.
3 0.89410806 1081 andrew gelman stats-2011-12-24-Statistical ethics violation
Introduction: A colleague writes: When I was in NYC I went to this party by group of Japanese bio-scientists. There, one guy told me about how the biggest pharmaceutical company in Japan did their statistics. They ran 100 different tests and reported the most significant one. (This was in 2006 and he said they stopped doing this few years back so they were doing this until pretty recently…) I’m not sure if this was 100 multiple comparison or 100 different kinds of test but I’m sure they wouldn’t want to disclose their data… Ouch!
4 0.86333048 945 andrew gelman stats-2011-10-06-W’man < W’pedia, again
Introduction: Blogger Deep Climate looks at another paper by the 2002 recipient of the American Statistical Association’s Founders award. This time it’s not funny, it’s just sad. Here’s Wikipedia on simulated annealing: By analogy with this physical process, each step of the SA algorithm replaces the current solution by a random “nearby” solution, chosen with a probability that depends on the difference between the corresponding function values and on a global parameter T (called the temperature), that is gradually decreased during the process. The dependency is such that the current solution changes almost randomly when T is large, but increasingly “downhill” as T goes to zero. The allowance for “uphill” moves saves the method from becoming stuck at local minima—which are the bane of greedier methods. And here’s Wegman: During each step of the algorithm, the variable that will eventually represent the minimum is replaced by a random solution that is chosen according to a temperature
5 0.8624931 241 andrew gelman stats-2010-08-29-Ethics and statistics in development research
Introduction: From Bannerjee and Duflo, “The Experimental Approach to Development Economics,” Annual Review of Economics (2009): One issue with the explicit acknowledgment of randomization as a fair way to allocate the program is that implementers may find that the easiest way to present it to the community is to say that an expansion of the program is planned for the control areas in the future (especially when such is indeed the case, as in phased-in design). I can’t quite figure out whether Bannerjee and Duflo are saying that they would lie and tell people that an expansion is planned when it isn’t, or whether they’re deploring that other people do it. I’m not bothered by a lot of the deception in experimental research–for example, I think the Milgram obedience experiment was just fine–but somehow the above deception bothers me. It just seems wrong to tell people that an expansion is planned if it’s not. P.S. Overall the article is pretty good. My only real problem with it is that
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