andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1238 knowledge-graph by maker-knowledge-mining
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Introduction: Several months ago, Sam Behseta, the new editor of Chance magazine, asked me if I’d like to have a column. I said yes, I’d like to write on ethics and statistics. My first column was called “Open Data and Open Methods” and I discussed the ethical obligation to share data and make our computations transparent wherever possible. In my column, I recounted a story from a bit over 20 years ago when I noticed a problem in a published analysis (involving electromagnetic fields and calcium flow in chicken brains) and contacted the researcher in charge of the study, who would not share his data with me. Two of the people from that research team—biologist Carl Blackman and statistician Dennis House—saw my Chance column and felt that I had misrepresented the situation and had criticized them unfairly. Blackman and House expressed their concerns in letters to the editor which were just published, along with my reply, in the latest issue of Chance . Seeing as I posted my article here, I
sentIndex sentText sentNum sentScore
1 Several months ago, Sam Behseta, the new editor of Chance magazine, asked me if I’d like to have a column. [sent-1, score-0.137]
2 I said yes, I’d like to write on ethics and statistics. [sent-2, score-0.247]
3 My first column was called “Open Data and Open Methods” and I discussed the ethical obligation to share data and make our computations transparent wherever possible. [sent-3, score-0.871]
4 In my column, I recounted a story from a bit over 20 years ago when I noticed a problem in a published analysis (involving electromagnetic fields and calcium flow in chicken brains) and contacted the researcher in charge of the study, who would not share his data with me. [sent-4, score-0.769]
5 Two of the people from that research team—biologist Carl Blackman and statistician Dennis House—saw my Chance column and felt that I had misrepresented the situation and had criticized them unfairly. [sent-5, score-0.389]
6 Blackman and House expressed their concerns in letters to the editor which were just published, along with my reply, in the latest issue of Chance . [sent-6, score-0.571]
7 I encourage all of you who are interested in ethics and data sharing to take a look. [sent-9, score-0.572]
8 As I wrote in my response, I appreciate the letters of Dr. [sent-10, score-0.353]
9 House and I hope that readers will benefit from seeing both their perspectives and mine—just as researchers in general can benefit from seeing multiple analyses of publicly shared data. [sent-12, score-0.892]
10 Please don’t put any criticisms of Blackman or House (or me! [sent-15, score-0.135]
11 I appreciate that they put in the effort to respond, and my purpose in posting their letters here is to give a forum for their views. [sent-17, score-0.633]
12 General comments about ethics and data sharing would be fine, but no need to focus on this particular case. [sent-18, score-0.496]
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Introduction: Several months ago, Sam Behseta, the new editor of Chance magazine, asked me if I’d like to have a column. I said yes, I’d like to write on ethics and statistics. My first column was called “Open Data and Open Methods” and I discussed the ethical obligation to share data and make our computations transparent wherever possible. In my column, I recounted a story from a bit over 20 years ago when I noticed a problem in a published analysis (involving electromagnetic fields and calcium flow in chicken brains) and contacted the researcher in charge of the study, who would not share his data with me. Two of the people from that research team—biologist Carl Blackman and statistician Dennis House—saw my Chance column and felt that I had misrepresented the situation and had criticized them unfairly. Blackman and House expressed their concerns in letters to the editor which were just published, along with my reply, in the latest issue of Chance . Seeing as I posted my article here, I
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Introduction: My new Chance ethics column (cowritten with Eric Loken). Click through and take a look. It’s a short article and I really like it. And here’s more Chance.
Introduction: I’ve recently started a regular column on ethics, appearing every three months in Chance magazine . My first column, “Open Data and Open Methods,” is here , and my second column, “Statisticians: When we teach, we don’t practice what we preach” (coauthored with Eric Loken) will be appearing in the next issue. Statistical ethics is a wide-open topic, and I’d be very interested in everyone’s thoughts, questions, and stories. I’d like to get beyond generic questions such as, Is it right to do a randomized trial when you think the treatment is probably better than the control?, and I’d also like to avoid the really easy questions such as, Is it ethical to copy Wikipedia entries and then sell the resulting publication for $2800 a year? [Note to people who are sick of hearing about this particular story: I'll consider stopping my blogging on it, the moment that the people involved consider apologizing for their behavior.] Please insert your thoughts, questions, stories, links, et
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Introduction: Part 1. The ideal policy Basbøll, as always, gets right to the point: Andrew Gelman is not the plagiarism police because there is no such thing as the plagiarism police. But, he continues: There is, at any self-respecting university and any self-respecting academic journal, a plagiarism policy, and there sure as hell is a “morality” of writing in the world of scholarship. The cardinal rule is: don’t use other people’s words or ideas without attributing those words or ideas to the people you got them from. What to do when the plagiarism (or, perhaps, sloppy quotation, to use a less loaded word) comes to light? Everyone makes mistakes, but if you make one you have to correct it. Don’t explain why your mistake isn’t very serious or “set things right” by pointing to the “obvious” signs of your good intentions. . . . Don’t say you’ve cleared it with the original author. The real victim of your crime is not the other writer; it’s your reader. That’s whose trust you’ve be
Introduction: David Karger writes: Your recent post on sharing data was of great interest to me, as my own research in computer science asks how to incentivize and lower barriers to data sharing. I was particularly curious about your highlighting of effort as the major dis-incentive to sharing. I would love to hear more, as this question of effort is on we specifically target in our development of tools for data authoring and publishing. As a straw man, let me point out that sharing data technically requires no more than posting an excel spreadsheet online. And that you likely already produced that spreadsheet during your own analytic work. So, in what way does such low-tech publishing fail to meet your data sharing objectives? Our own hypothesis has been that the effort is really quite low, with the problem being a lack of *immediate/tangible* benefits (as opposed to the long-term values you accurately describe). To attack this problem, we’re developing tools (and, since it appear
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same-blog 1 0.94262123 1238 andrew gelman stats-2012-03-31-Dispute about ethics of data sharing
Introduction: Several months ago, Sam Behseta, the new editor of Chance magazine, asked me if I’d like to have a column. I said yes, I’d like to write on ethics and statistics. My first column was called “Open Data and Open Methods” and I discussed the ethical obligation to share data and make our computations transparent wherever possible. In my column, I recounted a story from a bit over 20 years ago when I noticed a problem in a published analysis (involving electromagnetic fields and calcium flow in chicken brains) and contacted the researcher in charge of the study, who would not share his data with me. Two of the people from that research team—biologist Carl Blackman and statistician Dennis House—saw my Chance column and felt that I had misrepresented the situation and had criticized them unfairly. Blackman and House expressed their concerns in letters to the editor which were just published, along with my reply, in the latest issue of Chance . Seeing as I posted my article here, I
Introduction: I’ve recently started a regular column on ethics, appearing every three months in Chance magazine . My first column, “Open Data and Open Methods,” is here , and my second column, “Statisticians: When we teach, we don’t practice what we preach” (coauthored with Eric Loken) will be appearing in the next issue. Statistical ethics is a wide-open topic, and I’d be very interested in everyone’s thoughts, questions, and stories. I’d like to get beyond generic questions such as, Is it right to do a randomized trial when you think the treatment is probably better than the control?, and I’d also like to avoid the really easy questions such as, Is it ethical to copy Wikipedia entries and then sell the resulting publication for $2800 a year? [Note to people who are sick of hearing about this particular story: I'll consider stopping my blogging on it, the moment that the people involved consider apologizing for their behavior.] Please insert your thoughts, questions, stories, links, et
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Introduction: Yes, it can be done : Hereby I contact you to clarify the situation that occurred with the publication of the article entitled *** which was published in Volume 11, Issue 3 of *** and I made the mistake of declaring as an author. This chapter is a plagiarism of . . . I wish to express and acknowledge that I am solely responsible for this . . . I recognize the gravity of the offense committed, since there is no justification for so doing. Therefore, and as a sign of shame and regret I feel in this situation, I will publish this letter, in order to set an example for other researchers do not engage in a similar error. No more, and to please accept my apologies, Sincerely, *** P.S. Since we’re on Retraction Watch already, I’ll point you to this unrelated story featuring a hilarious photo of a fraudster, who in this case was a grad student in psychology who faked his data and “has agreed to submit to a three-year supervisory period for any work involving funding from the
4 0.68339372 2148 andrew gelman stats-2013-12-25-Spam!
Introduction: This one totally faked me out at first. It was an email from “Nick Bagnall” that began: Dear Dr. Gelman, I made contact last year regarding your work in the CMG: Reconstructing Climate from Tree Ring Data project. We are about to start producing the 2014 edition and I wanted to discuss this with you as we still remain keen to feature your work. Research Media are producing a special publication in February of 2014, within this report we will be working with a small selected number of PI’s with a focus on geosciences, atmospheric and geospace sciences and earth Sciences.. At this point, I’m thinking: Hmmm, I don’t remember this guy, is this some sort of collaborative project that I’d forgotten about? The message then continues: The publication is called International Innovation . . . Huh? This doesn’t sound so good. The email then goes on with some very long lists, and then finally the kicker: The total cost for each article produced in this report is fixed a
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Introduction: Betsey Stevenson and Justin Wolfers have been inspired by the recent Reinhardt and Rogoff debacle to list “six ways to separate lies from statistics” in economics research: 1. “Focus on how robust a finding is, meaning that different ways of looking at the evidence point to the same conclusion.” 2. Don’t confuse statistical with practical significance. 3. “Be wary of scholars using high-powered statistical techniques as a bludgeon to silence critics who are not specialists.” 4. “Don’t fall into the trap of thinking about an empirical finding as ‘right’ or ‘wrong.’ At best, data provide an imperfect guide.” 5. “Don’t mistake correlation for causation.” 6. “Always ask ‘so what?’” I like all these points, especially #4, which I think doesn’t get said enough. As I wrote a few months ago, high-profile social science research aims for proof, not for understanding—and that’s a problem. My addition to the list If you compare my title above to that of Stevenson
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Introduction: I was pleasantly surprised to have my recreational reading about baseball in the New Yorker interrupted by a digression on statistics. Sam Fuld of the Tampa Bay Rays, was the subjet of a Ben McGrath profile in the 4 July 2011 issue of the New Yorker , in an article titled Super Sam . After quoting a minor-league trainer who described Fuld as “a bit of a geek” (who isn’t these days?), McGrath gets into that lovely New Yorker detail: One could have pointed out the more persuasive and telling examples, such as the fact that in 2005, after his first pro season, with the Class-A Peoria Chiefs, Fuld applied for a fall internship with Stats, Inc., the research firm that supplies broadcasters with much of the data anad analysis that you hear in sports telecasts. After a description of what they had him doing, reviewing footage of games and cataloguing, he said “I thought, They have a stat for everything, but they don’t have any stats regarding foul balls.” Fuld’s
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Introduction: John Keltz writes: What do you think about curved lines connecting discrete data-points? (For example, here .) The problem with the smoothed graph is it seems to imply that something is going on in between the discrete data points, which is false. However, the straight-line version isn’t representing actual events either- it is just helping the eye connect each point. So maybe the curved version is also just helping the eye connect each point, and looks better doing it. In my own work (value-added modeling of achievement test scores) I use straight lines, but I guess I am not too bothered when people use smoothing. I’d appreciate your input. Regular readers will be unsurprised that, yes, I have an opinion on this one, and that this opinion is connected to some more general ideas about statistical graphics. In general I’m not a fan of the curved lines. They’re ok, but I don’t really see the point. I can connect the dots just fine without the curves. The more general id
Introduction: Someone passed on to a message from his university library announcing that the journal “Wiley Interdisciplinary Reviews: Computational Statistics” is no longer free. Librarians have to decide what to do, so I thought I’d offer the following consumer guide: Wiley Computational Statistics journal Wikipedia Frequency 6 issues per year Continuously updated Includes articles from Wikipedia? Yes Yes Cites the Wikipedia sources it uses? No Yes Edited by recipient of ASA Founders Award? Yes No Articles are subject to rigorous review? No Yes Errors, when discovered, get fixed? No Yes Number of vertices in n-dimensional hypercube? 2n 2 n Easy access to Brady Bunch trivia? No Yes Cost (North America) $1400-$2800 $0 Cost (UK) £986-£1972 £0 Cost (Europe) €1213-€2426 €0 The choice seems pretty clear to me! It’s funny for the Wiley journal to start charging now
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Introduction: Our “arm” package in R requires Doug Bates’s “lme4″ which fits multilevel models. lme4 is currently having some problems on the Mac. But installation on the Mac can be done; it just takes a bit of work. I have two sets of instructions below. From Yu-Sung: If you have MAC OS DVD, you should install developer X code packages from it. Otherwise, install them from here . After this, do the following in R: install.packages(“lme4″, type = “source”) Then you will have lme4 in R and you can install arm without a problem. And, from David Ozonoff: I installed the lme4 package via the Package Installer but this didn’t work, of course. I then installed, via this link , gfortran which seemed to put the libraries in the right place (I had earlier installed via Fink the gcc42 compiler, so I’m not sure if this is required or not). I then ran, in R, this: install.packages(c(“Matrix”,”lme4″), repos=”http://R-Forge.R-project.org”) This does not appear to work since it wi
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Introduction: How am I supposed to handle this sort of thing? (See below.) I just stuck it one of my email folders without responding, but then I wondered . . . what’s it all about? Is there some sort of Glengarry Glen Ross-like parallel world where down-on-their-luck Jack Lemmons of public relations world send out electronic cold calls? More than anything else, this sort of thing makes me glad I have a steady job. Here’s the (unsolicited) email, which came with the subject line “Please help a reporter do his job”: Dear Andrew, As an Editor for the Bulldog Reporter (www.bulldogreporter.com/dailydog), a media relations trade publication, my job is to help ensure that my readers have accurate info about you and send you the best quality pitches. By taking five minutes or less to answer my questions (pasted below), you’ll receive targeted PR pitches from our client base that will match your beat and interests. Any help or direction is appreciated. Here are my questions. We have you listed
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