andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1766 knowledge-graph by maker-knowledge-mining
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Introduction: Zosia Chustecka writes : Much of the previous work on the link between cancer and nightshifts has focused on breast cancer . . . The latest report, focusing on ovarian cancer, was published in the April issue of Occupational and Environmental Medicine. This increase in the risk for ovarian cancer with nightshift work is consistent with, and of similar magnitude to, the risk for breast cancer, say lead author Parveen Bhatti, PhD, and colleagues from the epidemiology program at the Fred Hutchinson Cancer Research Center in Seattle, Washington. The researchers examined data from a local population-based cancer registry that is part of the Surveillance Epidemiology and End Results (SEER) Program. They identified 1101 women with advanced epithelial ovarian cancer, 389 with borderline disease, and 1832 without ovarian cancer (control group). The women, who were 35 to 74 years of age, were asked about the hours they worked, and specifically whether they had ever worked the nig
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1 Zosia Chustecka writes : Much of the previous work on the link between cancer and nightshifts has focused on breast cancer . [sent-1, score-1.044]
2 The latest report, focusing on ovarian cancer, was published in the April issue of Occupational and Environmental Medicine. [sent-4, score-0.404]
3 This increase in the risk for ovarian cancer with nightshift work is consistent with, and of similar magnitude to, the risk for breast cancer, say lead author Parveen Bhatti, PhD, and colleagues from the epidemiology program at the Fred Hutchinson Cancer Research Center in Seattle, Washington. [sent-5, score-1.625]
4 The researchers examined data from a local population-based cancer registry that is part of the Surveillance Epidemiology and End Results (SEER) Program. [sent-6, score-0.677]
5 They identified 1101 women with advanced epithelial ovarian cancer, 389 with borderline disease, and 1832 without ovarian cancer (control group). [sent-7, score-1.662]
6 The women, who were 35 to 74 years of age, were asked about the hours they worked, and specifically whether they had ever worked the nightshift. [sent-8, score-0.305]
7 6% of the women with invasive cancer had worked nights at some point, as had 32. [sent-10, score-1.032]
8 In the entire cohort, the median duration of nightshift work was 2. [sent-13, score-0.382]
9 The most common types of nightshift jobs were in healthcare, food preparation and service, and office and admin support. [sent-16, score-0.448]
10 I hadn’t known so many people worked night shifts, but I guess these numbers make sense given that they’re asking people whether they’d ever worked nights. [sent-17, score-0.515]
11 I taught a night class for a couple of semesters. [sent-19, score-0.159]
12 [From comments: No, my evening class wouldn't count, they define nightshift as "the hours between midnight and 04:00. [sent-20, score-0.578]
13 " In that case, I didn't realize so many people had worked in such jobs. [sent-21, score-0.18]
14 ] Here’s the punchline: The researchers conclude that working nights is associated with an increased risk for both invasive ovarian cancer (odds ratio [OR], 1. [sent-22, score-1.34]
15 The Bayesian in me suspects the true population odds ratios are on the low end of this range, and the Uri Simonsohn in me is suspicious that the low ends of these confidence intervals are so close to 1. [sent-29, score-0.391]
16 Indeed, a look at the statistical analysis section of the article suggests the researchers had various degrees of freedom which could induce small changes in the p-value. [sent-31, score-0.142]
17 I also worry about the sensitivity of their results to their choice of adjustments for pre-treatment variables. [sent-32, score-0.104]
18 Any particular study is a brick in the wall, it provides some information and future studies can give more. [sent-35, score-0.069]
19 I found the above news article via Google after reading this summary which sent me to a not-so-detailed unsigned news report that was not so detailed and had no link to the original study. [sent-38, score-0.449]
20 The unsigned report was attributed to HealthDay: “Daily Health News and Medical News for Licensing & Syndication. [sent-39, score-0.239]
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same-blog 1 1.0000001 1766 andrew gelman stats-2013-03-16-“Nightshifts Linked to Increased Risk for Ovarian Cancer”
Introduction: Zosia Chustecka writes : Much of the previous work on the link between cancer and nightshifts has focused on breast cancer . . . The latest report, focusing on ovarian cancer, was published in the April issue of Occupational and Environmental Medicine. This increase in the risk for ovarian cancer with nightshift work is consistent with, and of similar magnitude to, the risk for breast cancer, say lead author Parveen Bhatti, PhD, and colleagues from the epidemiology program at the Fred Hutchinson Cancer Research Center in Seattle, Washington. The researchers examined data from a local population-based cancer registry that is part of the Surveillance Epidemiology and End Results (SEER) Program. They identified 1101 women with advanced epithelial ovarian cancer, 389 with borderline disease, and 1832 without ovarian cancer (control group). The women, who were 35 to 74 years of age, were asked about the hours they worked, and specifically whether they had ever worked the nig
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Introduction: The (U.S.) “President’s Cancer Panel” has released its 2008-2009 annual report, which includes a cover letter that says “the true burden of environmentally induced cancer has been grossly underestimated.” The report itself discusses exposures to various types of industrial chemicals, some of which are known carcinogens, in some detail, but gives nearly no data or analysis to suggest that these exposures are contributing to significant numbers of cancers. In fact, there is pretty good evidence that they are not. The plot above shows age-adjusted cancer mortality for men, by cancer type, in the U.S. The plot below shows the same for women. In both cases, the cancers with the highest mortality rates are shown, but not all cancers (e.g. brain cancer is not shown). For what it’s worth, I’m not sure how trustworthy the rates are from the 1930s — it seems possible that reporting, autopsies, or both, were less careful during the Great Depression — so I suggest focusing on the r
Introduction: Aaron Carroll shoots down a politically-loaded claim about cancer survival. Lots of useful background from science reporter Sharon Begley: With the United States spending more on healthcare than any other country — $2.5 trillion, or just over $8,000 per capita, in 2009 — the question has long been, is it worth it? At least for spending on cancer, a controversial new study answers with an emphatic “yes.” . . . Experts shown an advance copy of the paper by Reuters argued that the tricky statistics of cancer outcomes tripped up the authors. “This study is pure folly,” said biostatistician Dr. Don Berry of MD Anderson Cancer Center in Houston. “It’s completely misguided and it’s dangerous. Not only are the authors’ analyses flawed but their conclusions are also wrong.” Ouch. Arguably the study shouldn’t be getting any coverage at all, but given that it’s in the news, it’s good to see it get shot down. I wonder if the authors will respond to Don Berry and say they’re sorr
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Introduction: Cassie Murdoch points to a report from a corporate survey: Sixty-two percent of U.S. employees say it’s not likely they or a family member will be diagnosed with a serious illness like cancer, a survey indicates. The Aflac WorkForces Report, a survey of nearly 1,900 benefits decision-makers and more than 6,100 U.S. workers, also indicated 55 percent said they were not very or not at all likely to be diagnosed with a chronic illness, such as heart disease or diabetes. Here are some actual statistics: The American Cancer Society, Cancer Facts & Figures 2012, said 1-in-3 women and 1-in-2 men will be diagnosed with cancer at some point in their lives, and the National Safety Council, Injury Facts 2011 edition, says more than 38.9 million injuries occur in a year requiring medical treatment. The American Heart Association, Heart Disease & Stroke Statistics 2012, said 1-in-6 U.S. deaths were caused by coronary heart disease, Tillman said. And some details on the survey:
5 0.11832047 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 :
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Introduction: Zosia Chustecka writes : Much of the previous work on the link between cancer and nightshifts has focused on breast cancer . . . The latest report, focusing on ovarian cancer, was published in the April issue of Occupational and Environmental Medicine. This increase in the risk for ovarian cancer with nightshift work is consistent with, and of similar magnitude to, the risk for breast cancer, say lead author Parveen Bhatti, PhD, and colleagues from the epidemiology program at the Fred Hutchinson Cancer Research Center in Seattle, Washington. The researchers examined data from a local population-based cancer registry that is part of the Surveillance Epidemiology and End Results (SEER) Program. They identified 1101 women with advanced epithelial ovarian cancer, 389 with borderline disease, and 1832 without ovarian cancer (control group). The women, who were 35 to 74 years of age, were asked about the hours they worked, and specifically whether they had ever worked the nig
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Introduction: “Even as you get near the upper reaches of the normal weight range, you begin to see increases in chronic diseases,” said JoAnn Manson, chief of the Division of Preventive Medicine, Brigham and Women’s Hospital, HMS Michael and Lee Bell Professor of Women’s Health, and HSPH professor of epidemiology. “It’s a clear gradient of increase.” Yeah, she would say that. Thin people. And then there’s Frank Hu, professor of nutrition at Harvard: The studies that Flegal [the author of the original study finding a negative correlation between body mass index and mortality] did use included many samples of people who were chronically ill, current smokers and elderly, according to Hu. These factors are associated with weight loss and increased mortality. In other words, people are not dying because they are slim, he said. They are slim because they are dying—of cancer or old age, for example. By doing a meta-analysis of studies that did not properly control for this bias, Flegal amplif
4 0.73772413 1160 andrew gelman stats-2012-02-09-Familial Linkage between Neuropsychiatric Disorders and Intellectual Interests
Introduction: When I spoke at Princeton last year, I talked with neuroscientist Sam Wang, who told me about a project he did surveying incoming Princeton freshmen about mental illness in their families. He and his coauthor Benjamin Campbell found some interesting results, which they just published : A link between intellect and temperament has long been the subject of speculation. . . . Studies of the artistically inclined report linkage with familial depression, while among eminent and creative scientists, a lower incidence of affective disorders is found. In the case of developmental disorders, a heightened prevalence of autism spectrum disorders (ASDs) has been found in the families of mathematicians, physicists, and engineers. . . . We surveyed the incoming class of 2014 at Princeton University about their intended academic major, familial incidence of neuropsychiatric disorders, and demographic variables. . . . Consistent with prior findings, we noticed a relation between intended academ
Introduction: I read this front-page New York Times article and was immediately suspicious. Here’s the story (from reporter Gina Kolata): Could exercise actually be bad for some healthy people? A well-known group of researchers, including one who helped write the scientific paper justifying national guidelines that promote exercise for all, say the answer may be a qualified yes. By analyzing data from six rigorous exercise studies involving 1,687 people, the group found that about 10 percent actually got worse on at least one of the measures related to heart disease: blood pressure and levels of insulin, HDL cholesterol or triglycerides. About 7 percent got worse on at least two measures. And the researchers say they do not know why. “It is bizarre,” said Claude Bouchard, lead author of the paper , published on Wednesday in the journal PLoS One . . . Dr. Michael Lauer, director of the Division of Cardiovascular Sciences at the National Heart, Lung, and Blood Institute, the lead federal
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1 0.9449259 1546 andrew gelman stats-2012-10-24-Hey—has anybody done this study yet?
Introduction: A few years ago I suggested a research project to study how Americans define themselves in terms of regional identity. For example, if you grew up in South Dakota but live in Washington, D.C., do you you call yourself a midwesterner, a westerner, a southerner, or what? The analogy is to the paper by Michael Hout on “How 4 million Irish immigrants became 40 million Irish Americans.” Contrary to expectations, it wasn’t about prolific breeding, it was about how people of mixed background choose to classify themselves.
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Introduction: Zosia Chustecka writes : Much of the previous work on the link between cancer and nightshifts has focused on breast cancer . . . The latest report, focusing on ovarian cancer, was published in the April issue of Occupational and Environmental Medicine. This increase in the risk for ovarian cancer with nightshift work is consistent with, and of similar magnitude to, the risk for breast cancer, say lead author Parveen Bhatti, PhD, and colleagues from the epidemiology program at the Fred Hutchinson Cancer Research Center in Seattle, Washington. The researchers examined data from a local population-based cancer registry that is part of the Surveillance Epidemiology and End Results (SEER) Program. They identified 1101 women with advanced epithelial ovarian cancer, 389 with borderline disease, and 1832 without ovarian cancer (control group). The women, who were 35 to 74 years of age, were asked about the hours they worked, and specifically whether they had ever worked the nig
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Introduction: Another stereotype is affirmed when I go on the U.K. rail system webpage and it repeatedly times out on me. At one point I have a browser open with the itinerary I’m interested in, and then awhile later I reopen the window (not clicking on anything on the page, just bringing the window up on the screen) but it’s timed out again. P.S. Yes, yes, I know that Amtrak is worse. Still, it’s amusing to see a confirmation that, at least in one respect, the British trains are as bad as they say.
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Introduction: Bernard Phiri writes: I am relatively new to glm models, anyhow, I am currently using your book “Data analysis using regression and multilevel/hierarchical models” (pages 109-115). I am using a Poisson GLM model to analyse an aerial census dataset of wild herbivores on a ranch in Kenya. In my analysis I have the following variables: 1. Outcome variable: count of wild herbivores sighted at a given location 2. Explanatory variable1: vegetation type i.e. type of vegetation of the grid in which animals were sighted (the ranch is divided into 1x1km grids) 3. Explanatory variable2: animal species e.g. eland, elephant, zebra etc 4. Exposure: proximity to water i.e. distance (km) to the nearest water point My questions are as follows: 1. Am I correct to include proximity to water point as an offset? I notice that in the example in your book the offset is a count, does this matter? 2. By including proximity to water in the model as an exposure am I correct to interpret th
5 0.91184008 1446 andrew gelman stats-2012-08-06-“And will pardon Paul Claudel, Pardons him for writing well”
Introduction: In our recent discussion of plagiarism and fake quotes, a commenter points to two recent posts by Mark Liberman ( here and here ) where Liberman links to about a zillion cases of journalists publishing quotes that were never said. He goes into some detail about two journalists from the New Yorker: Jared Diamond, who created quotes from a some dude in Papua New Guinea (ironically, one of Diamond’s accusers here is the widow of Stephen Jay Gould), and Janet Malcolm, who not only apparently falsified quotes by a subject of one of her articles, she also may have faked the notes for her interviews. I didn’t know that particular bit about Janet Malcolm, but I’ve felt very uncomfortable about her ever since she her apparent attempt to try to force a mistrial for a convicted killer. Between that case and her earlier The Journalist and the Murderer, Malcolm really does seem to have some sort of sympathy for people who kill their family members. She’s a good writer, but I still find
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