andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2356 knowledge-graph by maker-knowledge-mining
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Introduction: Mon: Why we hate stepwise regression Tues: Did you buy laundry detergent on their most recent trip to the store? Also comments on scientific publication and yet another suggestion to do a study that allows within-person comparisons Wed: All the Assumptions That Are My Life Thurs: Identifying pathways for managing multiple disturbances to limit plant invasions Fri: Statistically savvy journalism Sat: “Does researching casual marijuana use cause brain abnormalities?” Sun: Regression and causality and variable ordering
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same-blog 1 1.0 2356 andrew gelman stats-2014-06-02-On deck this week
Introduction: Mon: Why we hate stepwise regression Tues: Did you buy laundry detergent on their most recent trip to the store? Also comments on scientific publication and yet another suggestion to do a study that allows within-person comparisons Wed: All the Assumptions That Are My Life Thurs: Identifying pathways for managing multiple disturbances to limit plant invasions Fri: Statistically savvy journalism Sat: “Does researching casual marijuana use cause brain abnormalities?” Sun: Regression and causality and variable ordering
Introduction: Please answer the above question before reading on . . . I’m curious after reading Leif Nelson’s report that, based on research with Minah Jung, approximately 42% of the people they surveyed said they bought laundry detergent on their most recent trip to the store. I’m stunned that the number is so high. 42%??? That’s almost half the time. If we bought laundry detergent half the time we went to the store, our apartment would be stacked so full with the stuff, we wouldn’t be able to enter the door. I think we buy laundry detergent . . . ummm, how often? There are 40 of those little laundry packets in the box, we do laundry once a day, sometimes twice, let’s say 10 times a week, so this means we buy detergent about once every 4 weeks. We go to the store, hmmm, about once a day, let’s say 5 times a week to put our guess on the conservative side. So, 20 trips to the store for each purchase of detergent, that’s 5% of the time. Compared to us, lots of people must (a) go to
3 0.27382287 2348 andrew gelman stats-2014-05-26-On deck this week
Introduction: Mon: WAIC and cross-validation in Stan! Tues: A whole fleet of gremlins: Looking more carefully at Richard Tol’s twice-corrected paper, “The Economic Effects of Climate Change” Wed: Just wondering Thurs: When you believe in things that you don’t understand Fri: I posted this as a comment on a sociology blog Sat: “Building on theories used to describe magnets, scientists have put together a model that captures something very different . . .” Sun: Why we hate stepwise regression
4 0.22676529 2366 andrew gelman stats-2014-06-09-On deck this week
Introduction: Mon: I hate polynomials Tues: Spring forward, fall back, drop dead? Wed: Bayes in the research conversation Thurs: The health policy innovation center: how best to move from pilot studies to large-scale practice? Fri: Stroopy names Sat: He’s not so great in math but wants to do statistics and machine learning Sun: Comparing the full model to the partial model
5 0.21758018 2290 andrew gelman stats-2014-04-14-On deck this week
Introduction: Mon : Transitioning to Stan Tues : When you believe in things that you don’t understand Wed : Looking for Bayesian expertise in India, for the purpose of analysis of sarcoma trials Thurs : If you get to the point of asking, just do it. But some difficulties do arise . . . Fri : One-tailed or two-tailed? Sat : Index or indicator variables Sun : Fooled by randomness
6 0.2136997 2240 andrew gelman stats-2014-03-10-On deck this week: Things people sent me
7 0.21092066 2276 andrew gelman stats-2014-03-31-On deck this week
8 0.20315485 2321 andrew gelman stats-2014-05-05-On deck this week
9 0.19975242 2331 andrew gelman stats-2014-05-12-On deck this week
10 0.18337865 2357 andrew gelman stats-2014-06-02-Why we hate stepwise regression
11 0.17373726 2253 andrew gelman stats-2014-03-17-On deck this week: Revisitings
12 0.16996181 1535 andrew gelman stats-2012-10-16-Bayesian analogue to stepwise regression?
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15 0.15818223 2285 andrew gelman stats-2014-04-07-On deck this week
16 0.1548309 2206 andrew gelman stats-2014-02-10-On deck this week
17 0.14501485 2222 andrew gelman stats-2014-02-24-On deck this week
18 0.13853838 2310 andrew gelman stats-2014-04-28-On deck this week
19 0.12810536 2214 andrew gelman stats-2014-02-17-On deck this week
20 0.12278438 2265 andrew gelman stats-2014-03-24-On deck this week
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same-blog 1 0.98071545 2356 andrew gelman stats-2014-06-02-On deck this week
Introduction: Mon: Why we hate stepwise regression Tues: Did you buy laundry detergent on their most recent trip to the store? Also comments on scientific publication and yet another suggestion to do a study that allows within-person comparisons Wed: All the Assumptions That Are My Life Thurs: Identifying pathways for managing multiple disturbances to limit plant invasions Fri: Statistically savvy journalism Sat: “Does researching casual marijuana use cause brain abnormalities?” Sun: Regression and causality and variable ordering
2 0.82630885 2290 andrew gelman stats-2014-04-14-On deck this week
Introduction: Mon : Transitioning to Stan Tues : When you believe in things that you don’t understand Wed : Looking for Bayesian expertise in India, for the purpose of analysis of sarcoma trials Thurs : If you get to the point of asking, just do it. But some difficulties do arise . . . Fri : One-tailed or two-tailed? Sat : Index or indicator variables Sun : Fooled by randomness
3 0.8193621 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 0.81773669 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 0.81178558 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
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9 0.72910345 2214 andrew gelman stats-2014-02-17-On deck this week
10 0.71979338 2253 andrew gelman stats-2014-03-17-On deck this week: Revisitings
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17 0.56915218 165 andrew gelman stats-2010-07-27-Nothing is Linear, Nothing is Additive: Bayesian Models for Interactions in Social Science
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20 0.54257429 679 andrew gelman stats-2011-04-25-My talk at Stanford on Tuesday
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same-blog 1 0.94820905 2356 andrew gelman stats-2014-06-02-On deck this week
Introduction: Mon: Why we hate stepwise regression Tues: Did you buy laundry detergent on their most recent trip to the store? Also comments on scientific publication and yet another suggestion to do a study that allows within-person comparisons Wed: All the Assumptions That Are My Life Thurs: Identifying pathways for managing multiple disturbances to limit plant invasions Fri: Statistically savvy journalism Sat: “Does researching casual marijuana use cause brain abnormalities?” Sun: Regression and causality and variable ordering
2 0.84932262 2067 andrew gelman stats-2013-10-18-EP and ABC
Introduction: Expectation propagation and approximate Bayesian computation. Here are X’s comments on a paper, “Expectation-Propagation for Likelihood-Free Inference,” by Simon Barthelme and Nicolas Chopin. The paper is not new but the topic is still hot. Also there’s this paper by Maurizio Filippone and Mark Girolami on computation for Gaussian process models. I wonder how this connects to GPstuff , which I think is what Aki did to fit the birthdays model: This stuff is where it’s at.
Introduction: I’m sorry I don’t have any new zombie papers in time for Halloween. Instead I’d like to be a little monster by reproducing a mini-rant from this article on experimental reasoning in social science: I will restrict my discussion to social science examples. Social scientists are often tempted to illustrate their ideas with examples from medical research. When it comes to medicine, though, we are, with rare exceptions, at best ignorant laypersons (in my case, not even reaching that level), and it is my impression that by reaching for medical analogies we are implicitly trying to borrow some of the scientific and cultural authority of that field for our own purposes. Evidence-based medicine is the subject of a large literature of its own (see, for example, Lau, Ioannidis, and Schmid, 1998).
4 0.83052963 1856 andrew gelman stats-2013-05-14-GPstuff: Bayesian Modeling with Gaussian Processes
Introduction: I think it’s part of my duty as a blogger to intersperse, along with the steady flow of jokes, rants, and literary criticism, some material that will actually be useful to you. So here goes. Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, and Aki Vehtari write : The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for Bayesian inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods. We can actually now fit Gaussian processes in Stan . But for big problems (or even moderately-sized problems), full Bayes can be slow. GPstuff uses EP, which is faster. At some point we’d like to implement EP in Stan. (Right now we’re working with Dave Blei to implement VB.) GPstuff really works. I saw Aki use it to fit a nonparametric version of the Bangladesh well-switching example in ARM. He was sitting in his office and just whip
5 0.83009553 1047 andrew gelman stats-2011-12-08-I Am Too Absolutely Heteroskedastic for This Probit Model
Introduction: Soren Lorensen wrote: I’m working on a project that uses a binary choice model on panel data. Since I have panel data and am using MLE, I’m concerned about heteroskedasticity making my estimates inconsistent and biased. Are you familiar with any statistical packages with pre-built tests for heteroskedasticity in binary choice ML models? If not, is there value in cutting my data into groups over which I guess the error variance might vary and eyeballing residual plots? Have you other suggestions about how I might resolve this concern? I replied that I wouldn’t worry so much about heteroskedasticity. Breaking up the data into pieces might make sense, but for the purpose of estimating how the coefficients might vary—that is, nonlinearity and interactions. Soren shot back: I’m somewhat puzzled however: homoskedasticity is an identifying assumption in estimating a probit model: if we don’t have it all sorts of bad things can happen to our parameter estimates. Do you suggest n
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