andrew_gelman_stats andrew_gelman_stats-2014 andrew_gelman_stats-2014-2199 knowledge-graph by maker-knowledge-mining
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Introduction: Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts.” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. Or, just move the norm (center) so as to pick up a much larger number of patients. Afflictions include hypertension, cholesterol, overweight, osteoporosis. The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. H. Gilbert Welch has written extensively on this “goalpost” issue. He is the author of http://www.amazon.com/Overdiagnosed-Ma
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1 Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts. [sent-1, score-0.432]
2 ” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. [sent-2, score-1.302]
3 But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. [sent-3, score-0.54]
4 Or, just move the norm (center) so as to pick up a much larger number of patients. [sent-4, score-0.234]
5 The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. [sent-6, score-0.605]
6 Gilbert Welch has written extensively on this “goalpost” issue. [sent-8, score-0.132]
7 com/Overdiagnosed-Making-People-Pursuit-Health/dp/0807021997 He also has spoken on NPR http://www. [sent-11, score-0.121]
8 2C_overtreated See his pages 64 and 66 which shows graphs which illustrate how diagnoses increase markedly while deaths are flatlined. [sent-17, score-0.56]
9 The Guardian’s Ben Goldacre often writes about the goalpost issue. [sent-18, score-0.468]
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same-blog 1 1.0 2199 andrew gelman stats-2014-02-04-Widening the goalposts in medical trials
Introduction: Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts.” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. Or, just move the norm (center) so as to pick up a much larger number of patients. Afflictions include hypertension, cholesterol, overweight, osteoporosis. The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. H. Gilbert Welch has written extensively on this “goalpost” issue. He is the author of http://www.amazon.com/Overdiagnosed-Ma
2 0.18084496 2205 andrew gelman stats-2014-02-10-More on US health care overkill
Introduction: Paul Alper writes: You recently posted my moving and widening the goalposts contention. In it, I mentioned “how diagnoses increase markedly while deaths are flatlined” indicating that we are being overdiagnosed and overtreated. Above are 5 frightening graphs which illustrate the phenomenon. Defenders of the system might (ludicrously) contend that it is precisely the aggressive medical care that is responsible for keeping the cancers under control. The prostate cancer graph is particularly interesting because it shows the peaking of the PSA-driven cause of treatment in the 1990s which then falls off as the evidence accumulates that the PSA was far from a perfect indicator. In contrast is the thyroid cancer which zooms skyward even as the death rate is absolutely (dead) flat. And of course here’s the famous cross-country comparison that some find “ schlocky ” but which I (and many others) find compelling :
3 0.12955844 411 andrew gelman stats-2010-11-13-Ethical concerns in medical trials
Introduction: I just read this article on the treatment of medical volunteers, written by doctor and bioethicist Carl Ellliott. As a statistician who has done a small amount of consulting for pharmaceutical companies, I have a slightly different perspective. As a doctor, Elliott focuses on individual patients, whereas, as a statistician, I’ve been trained to focus on the goal of accurately estimate treatment effects. I’ll go through Elliott’s article and give my reactions. Elliott: In Miami, investigative reporters for Bloomberg Markets magazine discovered that a contract research organisation called SFBC International was testing drugs on undocumented immigrants in a rundown motel; since that report, the motel has been demolished for fire and safety violations. . . . SFBC had recently been named one of the best small businesses in America by Forbes magazine. The Holiday Inn testing facility was the largest in North America, and had been operating for nearly ten years before inspecto
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Introduction: I sent the following email to Thomas Basbøll: I read this: http://secondlanguage.blogspot.com/p/writing-coach.html and was reminded of this: http://andrewgelman.com/2011/10/could-i-use-a-statistics-coach/ He replied: Which reminds me of this http://secondlanguage.blogspot.com/2011/10/teacher-or-coach.html We seem to be approaching some sort of Platonic ideal in which we can conduct an entire conversation from links to our previous writings. Just like that joke about the roomful of comedians who refer to jokes by their numbers.
5 0.080747813 2314 andrew gelman stats-2014-05-01-Heller, Heller, and Gorfine on univariate and multivariate information measures
Introduction: Malka Gorfine writes: We noticed that the important topic of association measures and tests came up again in your blog, and we have few comments in this regard. It is useful to distinguish between the univariate and multivariate methods. A consistent multivariate method can recognise dependence between two vectors of random variables, while a univariate method can only loop over pairs of components and check for dependency between them. There are very few consistent multivariate methods. To the best of our knowledge there are three practical methods: 1) HSIC by Gretton et al. (http://www.gatsby.ucl.ac.uk/~gretton/papers/GreBouSmoSch05.pdf) 2) dcov by Szekely et al. (http://projecteuclid.org/euclid.aoas/1267453933) 3) A method we introduced in Heller et al (Biometrika, 2013, 503—510, http://biomet.oxfordjournals.org/content/early/2012/12/04/biomet.ass070.full.pdf+html, and an R package, HHG, is available as well http://cran.r-project.org/web/packages/HHG/index.html). A
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same-blog 1 0.95511413 2199 andrew gelman stats-2014-02-04-Widening the goalposts in medical trials
Introduction: Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts.” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. Or, just move the norm (center) so as to pick up a much larger number of patients. Afflictions include hypertension, cholesterol, overweight, osteoporosis. The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. H. Gilbert Welch has written extensively on this “goalpost” issue. He is the author of http://www.amazon.com/Overdiagnosed-Ma
Introduction: After learning of a news article by Amy Harmon on problems with medical trials–sometimes people are stuck getting the placebo when they could really use the experimental treatment, and it can be a life-or-death difference, John Langford discusses some fifteen-year-old work on optimal design in machine learning and makes the following completely reasonable point: With reasonable record keeping of existing outcomes for the standard treatments, there is no need to explicitly assign people to a control group with the standard treatment, as that approach is effectively explored with great certainty. Asserting otherwise would imply that the nature of effective treatments for cancer has changed between now and a year ago, which denies the value of any clinical trial. . . . Done the right way, the clinical trial for a successful treatment would start with some initial small pool (equivalent to “phase 1″ in the article) and then simply expanded the pool of participants over time as it
3 0.67385972 314 andrew gelman stats-2010-10-03-Disconnect between drug and medical device approval
Introduction: Sanjay Kaul wrotes: By statute (“the least burdensome” pathway), the approval standard for devices by the US FDA is lower than for drugs. Before a new drug can be marketed, the sponsor must show “substantial evidence of effectiveness” as based on two or more well-controlled clinical studies (which literally means 2 trials, each with a p value of <0.05, or 1 large trial with a robust p value <0.00125). In contrast, the sponsor of a new device, especially those that are designated as high-risk (Class III) device, need only demonstrate "substantial equivalence" to an FDA-approved device via the 510(k) exemption or a "reasonable assurance of safety and effectiveness", evaluated through a pre-market approval and typically based on a single study. What does “reasonable assurance” or “substantial equivalence” imply to you as a Bayesian? These are obviously qualitative constructs, but if one were to quantify them, how would you go about addressing it? The regulatory definitions for
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Introduction: Brett Keller points to a recent news article by Sharon Begley and Robin Respaut: A lot of doctors, hospitals and other healthcare providers in the United States decline to treat people who can’t pay, or have inadequate insurance, among other reasons. What sets CTCA [Cancer Treatment Centers of America] apart is that rejecting certain patients and, even more, culling some of its patients from its survival data lets the company tout in ads and post on its website patient outcomes that look dramatically better than they would if the company treated all comers. These are the rosy survival numbers . . . Details: CTCA reports on its website that the percentage of its patients who are alive after six months, a year, 18 months and longer regularly tops national figures. For instance, 60 percent of its non-small-cell lung cancer patients are alive at six months, CTCA says, compared to 38 percent nationally. And 64 percent of its prostate cancer patients are alive at three years, vers
Introduction: Paul Alper writes: You recently posted on graphs and how to convey information. I don’t believe you have ever posted anything on this dynamite randomized clinical trial of 90,000 (!!) 40-59 year-old women over a 25-year period (also !!). The graphs below are figures 2, 3 and 4 respectively, of http://www.bmj.com/content/348/bmj.g366 The control was physical exam only and the treatment was physical exam plus mammography. The graph clearly shows that mammography adds virtually nothing to survival and if anything, decreases survival (and increases cost and provides unnecessary treatment). Note the superfluousness of the p-values. There is an accompanying editorial in the BMJ http://www.bmj.com/content/348/bmj.g1403 which refers to “vested interests” which can override any statistics, no matter how striking: We agree with Miller and colleagues that “the rationale for screening by mammography be urgently reassessed by policy makers.” As time goes
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1 0.94486392 1291 andrew gelman stats-2012-04-30-Systematic review of publication bias in studies on publication bias
Introduction: Via Yalda Afshar , a 2005 paper by Hans-Hermann Dubben and Hans-Peter Beck-Bornholdt: Publication bias is a well known phenomenon in clinical literature, in which positive results have a better chance of being published, are published earlier, and are published in journals with higher impact factors. Conclusions exclusively based on published studies, therefore, can be misleading. Selective under-reporting of research might be more widespread and more likely to have adverse consequences for patients than publication of deliberately falsified data. We investigated whether there is preferential publication of positive papers on publication bias. They conclude, “We found no evidence of publication bias in reports on publication bias.” But of course that’s the sort of finding regarding publication bias of findings on publication bias that you’d expect would get published. What we really need is a careful meta-analysis to estimate the level of publication bias in studies of publi
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Introduction: Paul Alper writes: I do not believe your blog has ever dealt with the following phenomenon which might be called “(widening) moving the goalposts.” Drug companies and the medical world at large often create powerful drugs and procedures for people who are far (many standard deviations) from the norm (mean) and via randomized clinical trials, the relevant authorities approve. But there aren’t enough of those people to be truly profitable so the next step is to ask for approval to prescribe the same for people who aren’t that far (fewer standard deviations) from the norm. Or, just move the norm (center) so as to pick up a much larger number of patients. Afflictions include hypertension, cholesterol, overweight, osteoporosis. The result is what is often called “the worried well,” who receive little or no benefit but suffer harms from the treatment. H. Gilbert Welch has written extensively on this “goalpost” issue. He is the author of http://www.amazon.com/Overdiagnosed-Ma
3 0.93752062 529 andrew gelman stats-2011-01-21-“City Opens Inquiry on Grading Practices at a Top-Scoring Bronx School”
Introduction: Sharon Otterman reports : When report card grades were released in the fall for the city’s 455 high schools, the highest score went to a small school in a down-and-out section of the Bronx . . . A stunning 94 percent of its seniors graduated, more than 30 points above the citywide average. . . . “When I interviewed for the school,” said Sam Buchbinder, a history teacher, “it was made very clear: this is a school that doesn’t believe in anyone failing.” That statement was not just an exhortation to excellence. It was school policy. By order of the principal, codified in the school’s teacher handbook, all teachers should grade their classes in the same way: 30 percent of students should earn a grade in the A range, 40 percent B’s, 25 percent C’s, and no more than 5 percent D’s. As long as they show up, they should not fail. Hey, that sounds like Harvard and Columbia^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H^H various selective northeastern colleges I’ve known. Of course, we^H^H
4 0.92515451 1532 andrew gelman stats-2012-10-13-A real-life dollar auction game!
Introduction: Actually, $100,000 auction. I learned about it after seeing the following email which was broadcast to a couple of mailing lists: Dear all, I am now writing about something completely different! I need your help “voting” for our project, and sending this e-mail to others so that they can also vote for our project. As you will see from the video, the project would fund *** Project: I am a finalist for a $100,000 prize from Brigham and Women’s Hospital. My project is to understand how ***. Ultimately, we want to develop a ***. We expect that this ** can be used to *** Here are the instructions: 1. Go to the web page: http://brighamandwomens.org/research/BFF/default.aspx 2. scroll to the bottom and follow the link to “Vote” 3. select project #** 4. FORWARD THIS E-MAIL TO AS MANY PEOPLE AS YOU CAN. Best regards, ** I love that step 4 is in ALL CAPS, just to give it that genuine chain-letter aura. Isn’t this weird? First, that this foundation would give ou
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Introduction: 1. Congress vs. Nickelback: The real action is in the cross tabs : Conservatives are mean, liberals are big babies, and, if supporting an STD is what it takes to be a political moderate, I don’t want to be one. 2. How 2012 stacks up: The worst graph on record? : OK, not actually worse than this one . 3. Boys will be boys; cows will be cows : Children’s essentialist reasoning about gender categories and animal species.
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