andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1217 knowledge-graph by maker-knowledge-mining
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Introduction: David Hogg points me to this announcement of a program from the National Center for Science and Engineering Statistics of the National Science Foundation: The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise. This sounds like a job for Mister P. My first thought when David sent this to me was not to post it, because maybe I’d want to apply myself! But then I thought better of my piggy instincts, so here it is. I think some of the readers of this blog are doing research that would be relevant for this program, so . . . go for it!
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2 My first thought when David sent this to me was not to post it, because maybe I’d want to apply myself! [sent-4, score-0.474]
3 But then I thought better of my piggy instincts, so here it is. [sent-5, score-0.369]
4 I think some of the readers of this blog are doing research that would be relevant for this program, so . [sent-6, score-0.442]
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same-blog 1 0.99999988 1217 andrew gelman stats-2012-03-17-NSF program “to support analytic and methodological research in support of its surveys”
Introduction: David Hogg points me to this announcement of a program from the National Center for Science and Engineering Statistics of the National Science Foundation: The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise. This sounds like a job for Mister P. My first thought when David sent this to me was not to post it, because maybe I’d want to apply myself! But then I thought better of my piggy instincts, so here it is. I think some of the readers of this blog are doing research that would be relevant for this program, so . . . go for it!
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Introduction: Two positions open in the statistics group at the NYU education school. If you get the job, you get to work with Jennifer HIll! One position is a postdoctoral fellowship, and the other is a visiting professorship. The latter position requires “the demonstrated ability to develop a nationally recognized research program,” which seems like a lot to ask for a visiting professor. Do they expect the visiting prof to develop a nationally recognized research program and then leave it there at NYU after the visit is over? In any case, Jennifer and her colleagues are doing excellent work, both applied and methodological, and this seems like a great opportunity.
3 0.12953226 660 andrew gelman stats-2011-04-14-Job opening at NIH for an experienced statistician
Introduction: This announcement might be of interest to some of you. The application deadline is in just a few days: The National Center for Complementary and Alternative Medicine at the National Institutes of Health is seeking an additional experienced statistician to join our Office of Clinical and Regulatory Affairs team. www.usajobs.gov is accepting applications through April 22, 2011 for the general announcement and April 21 for status (typically current federal employee) candidates. To apply to this announcement or for more information, click on the links provided below or the USAJobs link provided above and search for NIH-NCCAM-DE-11-448747 ( external ) or NIH-NCCAM-MP-11-448766 ( internal ). You have to be a U.S. citizen for this one.
Introduction: One thing we do here at the Applied Statistics Center is hold mini-conferences. The next one looks really cool. It’s organized by Sharad Goel and Jake Hofman (Microsoft Research, formerly at Yahoo Research), David Park (Columbia University), and Sergei Vassilvitskii (Google). As with our other conferences, one of our goals is to mix the academic and nonacademic research communities. Here’s the website for the workshop, and here’s the announcement from the organizers: With an explosion of data on every aspect of our everyday existence — from what we buy, to where we travel, to who we know — we are able to observe human behavior with granularity largely thought impossible just a decade ago. The growth of such online activity has further facilitated the design of web-based experiments, enhancing both the scale and efficiency of traditional methods. Together these advances have created an unprecedented opportunity to address longstanding questions in the social sciences, rang
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Introduction: I received the following unsolicited email, subject line Technology and Engineering Research: Dear Editor We have done research in some of the cutting edge technology and engineering field and would like to if you will be able to write about it in your news section. Our Primarily research focus on building high performance systems that are helping in social networks, web, finding disease, cancer and sports using BIG DATA . Hope to hear from you some time soon. Thanks, ***, PhD Chartered Scientist IBM Corportation ***@us.ibm.com 916 *** **** I thought IBM was a professional operation—don’t they have their own public relations department?
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Introduction: David Hogg points me to this announcement of a program from the National Center for Science and Engineering Statistics of the National Science Foundation: The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise. This sounds like a job for Mister P. My first thought when David sent this to me was not to post it, because maybe I’d want to apply myself! But then I thought better of my piggy instincts, so here it is. I think some of the readers of this blog are doing research that would be relevant for this program, so . . . go for it!
Introduction: One thing we do here at the Applied Statistics Center is hold mini-conferences. The next one looks really cool. It’s organized by Sharad Goel and Jake Hofman (Microsoft Research, formerly at Yahoo Research), David Park (Columbia University), and Sergei Vassilvitskii (Google). As with our other conferences, one of our goals is to mix the academic and nonacademic research communities. Here’s the website for the workshop, and here’s the announcement from the organizers: With an explosion of data on every aspect of our everyday existence — from what we buy, to where we travel, to who we know — we are able to observe human behavior with granularity largely thought impossible just a decade ago. The growth of such online activity has further facilitated the design of web-based experiments, enhancing both the scale and efficiency of traditional methods. Together these advances have created an unprecedented opportunity to address longstanding questions in the social sciences, rang
Introduction: (1) Hop the Q-Train ! That is, the Columbia/NYU Quantitative Training Program, funded by the Institute of Education Sciences to create a cohort of postdoctoral scholars both to develop the new statistical methods required to meet future research challenges and to effectively train and consult with other education researchers. You’ll be working with Jennifer Hill, Marc Scott, and me on our exciting research projects, some of which are here ! Candidates must be United States citizens or permanent residents. For best consideration applications must be submitted before 15 Nov 2012. Please direct administrative inquiries to Jonathan Winters at jonathan.winters@nyu.edu and substantive inquiries to Jennifer or me. (2) The Earth Institute Postdoctoral Fellows program ! Every year a select group of recent Ph.D.s in a variety of fields come to the Earth Institute for this two-year research fellowship. I’d love to see more statisticians applying. To apply, candidates must compl
4 0.77880186 1904 andrew gelman stats-2013-06-18-Job opening! Come work with us!
Introduction: Postdoctoral position in statistical modeling of social networks A full-time postdoctoral position is available beginning Fall 2014 in the research group of Tian Zheng and Andrew Gelman working on statistical analysis and modeling of social network data, in close cooperation with our experimental collaborators. Four key papers of this project so far are: http://www.stat.columbia.edu/~gelman/research/published/overdisp_final.pdf http://nersp.osg.ufl.edu/~ufruss/documents/mccormick_salganik_zheng10.pdf http://www.stat.columbia.edu/~gelman/research/published/DiPreteetal.pdf http://arxiv.org/pdf/1301.2473.pdf Requirements: The work is highly interdisciplinary, and applicants must have strong statistical and computational skills. Social science research skills are preferred but not necessary. Preferred educational background is a PhD in statistics, computer science, political science, sociology, or a related field. Expertise in Bayesian modeling and computing is required. Prev
Introduction: Andrew Gelman (Columbia University) and Jennifer Hill (New York University) seek to hire a post-doctoral fellow to work on development of iterative imputation algorithms and diagnostics for missing-data imputation. Activities would include model-development, programming, and data analysis. This project is funded by a grant from the Institute of Education Sciences. Other collaborators on the project include Jingchen Liu and Ben Goodrich. This is a two-year position that would start this summer (2011) or earlier if possible. The ideal candidate will have a statistics or computer science background, will be interested in statistical modeling, serious programming, and applications. He or she should be able to work fluently in R and should already know about hierarchical models and Bayesian inference and computation. Experience or interest in designing GUIs would be a bonus, since we are attempting to improve our GUI for missing data imputation. The successful candidate will beco
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Introduction: Anna Lena Phillips writes : I. Many people will not, of their own accord, look at a poem. II. Millions of people will, of their own accord, spend lots and lots of time looking at photographs of cats. III. Therefore, earlier this year, I concluded that the best strategy for increasing the number of viewers for poems would be to print them on top of photographs of cats. IV. I happen to like looking at both poems and cats. V. So this is, for me, a win-win situation. VI. Fortunately, my own cat is a patient model, and (if I am to be believed) quite photogenic. VII. The aforementioned cat is Tisko Tansi, small hero. VII. Thus I present to you (albeit in digital rather than physical form) an Endearments broadside, featuring a poem that originally appeared in BlazeVOX spring 2011. VIII. If you want to share a copy of this image, please ask first. If you want a real copy, you can ask about that too. She follows up with an image of a cat, on which is superimposed a short
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Introduction: 10,000 iterations for 4 chains on the (precompiled) efficiently-parameterized 8-schools model: > date () [1] "Thu Aug 30 22:12:53 2012" > fit3 <- stan (fit=fit2, data = schools_dat, iter = 1e4, n_chains = 4) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 1). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 2). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 3). Iteration: 10000 / 10000 [100%] (Sampling) SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 4). Iteration: 10000 / 10000 [100%] (Sampling) > date () [1] "Thu Aug 30 22:12:55 2012" > print (fit3) Inference for Stan model: anon_model. 4 chains: each with iter=10000; warmup=5000; thin=1; 10000 iterations saved. mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat mu 8.0 0.1 5.1 -2.0 4.7 8.0 11.3 18.4 4032 1 tau 6.7 0.1 5.6 0.3 2.5 5.4 9.3 21.2 2958 1 eta[1] 0.4 0.0 0.9 -1.5 -0
3 0.95530468 1478 andrew gelman stats-2012-08-31-Watercolor regression
Introduction: Solomon Hsiang writes: Two small follow-ups based on the discussion (the second/bigger one is to address your comment about the 95% CI edges). 1. I realized that if we plot the confidence intervals as a solid color that fades (eg. using the “fixed ink” scheme from before) we can make sure the regression line also has heightened visual weight where confidence is high by plotting the line white. This makes the contrast (and thus visual weight) between the regression line and the CI highest when the CI is narrow and dark. As the CI fade near the edges, so does the contrast with the regression line. This is a small adjustment, but I like it because it is so simple and it makes the graph much nicer. (see “visually_weighted_fill_reverse” attached). My posted code has been updated to do this automatically. 2. You and your readers didn’t like that the edges of the filled CI were so sharp and arbitrary. But I didn’t like that the contrast between the spaghetti lines and the background
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Introduction: [Update: Revised given comments from Wingfeet, Andrew and germo. Thanks! I'd mistakenly translated the dlnorm priors in the first version --- amazing what a difference the priors make. I also escaped the less-than and greater-than signs in the constraints in the model so they're visible. I also updated to match the thin=2 output of JAGS.] We’re going to be starting a Stan “model of the P” (for some time period P) column, so I thought I’d kick things off with one of my own. I’ve been following the Wingvoet blog , the author of which is identified only by the Blogger handle Wingfeet ; a couple of days ago this lovely post came out: PK calculation of IV and oral dosing in JAGS Wingfeet’s post implemented an answer to question 6 from chapter 6 of problem from Rowland and Tozer’s 2010 book, Clinical Pharmacokinetics and Pharmacodynamics , Fourth edition, Lippincott, Williams & Wilkins. So in the grand tradition of using this blog to procrastinate, I thought I’d t
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Introduction: Washington Post and Slate reporter Anne Applebaum wrote a dismissive column about Wikileaks, saying that they “offer nothing more than raw data.” Applebaum argues that “The notion that the Internet can replace traditional news-gathering has just been revealed to be a myth. . . . without more journalism, more investigation, more work, these documents just don’t matter that much.” Fine. But don’t undervalue the role of mere data! The usual story is that we don’t get to see the raw data underlying newspaper stories. Wikileaks and other crowdsourced data can be extremely useful, whether or not they replace “traditional news-gathering.”
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