Posts Tagged ‘ Public Health ’

A reporter sent me a Jama paper and asked me what I thought . . .

December 10, 2017
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My reply: Thanks for sending. I can’t be sure about everything they’re doing but the paper looks reasonable to me. I expect there are various ways that the analysis could be improved, but on a quick look I don’t see anything obviously wrong with it, and the authors seem to know what they are doing. […] The post A reporter sent me a Jama paper and asked me what I…

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“How to Assess Internet Cures Without Falling for Dangerous Pseudoscience”

December 8, 2017
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Science writer Julie Rehmeyer discusses her own story: Five years ago, against practically anyone’s better judgment, I knowingly abandoned any semblance of medical evidence to follow the bizarre-sounding health advice of strangers on the internet. The treatment was extreme, expensive, and potentially dangerous. If that sounds like a terrible idea to you, imagine how it […] The post “How to Assess Internet Cures Without Falling for Dangerous Pseudoscience” appeared first…

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Orphan drugs and forking paths: I’d prefer a multilevel model but to be honest I’ve never fit such a model for this sort of problem

December 3, 2017
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Orphan drugs and forking paths:  I’d prefer a multilevel model but to be honest I’ve never fit such a model for this sort of problem

Amos Elberg writes: I’m writing to let you know about a drug trial you may find interesting from a statistical perspective. As you may know, the relatively recent “orphan drug” laws allow (basically) companies that can prove an off-patent drug treats an otherwise untreatable illness, to obtain intellectual property protection for otherwise generic or dead […] The post Orphan drugs and forking paths: I’d prefer a multilevel model but to…

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“A Bias in the Evaluation of Bias Comparing Randomized Trials with Nonexperimental Studies”

November 20, 2017
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“A Bias in the Evaluation of Bias Comparing Randomized Trials with Nonexperimental Studies”

Jessica Franklin writes: Given your interest in post-publication peer review, I thought you might be interested in our recent experience criticizing a paper published in BMJ last year by Hemkens et al.. I realized that the method used for the primary analysis was biased, so we published a criticism with mathematical proof of the bias […] The post “A Bias in the Evaluation of Bias Comparing Randomized Trials with Nonexperimental…

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Spatial models for demographic trends?

November 19, 2017
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Jon Minton writes: You may be interested in a commentary piece I wrote early this year, which was published recently in the International Journal of Epidemiology, where I discuss your work on identifying an aggregation bias in one of the key figures in Case & Deaton’s (in)famous 2015 paper on rising morbidity and mortality in […] The post Spatial models for demographic trends? appeared first on Statistical Modeling, Causal Inference,…

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Noisy, heterogeneous data scoured from diverse sources make his metanalyses stronger.

November 10, 2017
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Kyle MacDonald writes: I wondered if you’d heard of Purvesh Khatri’s work in computational immunology, profiled in this Q&A with Esther Landhuis at Quanta yesterday. Elevator pitch is that he believes noisy, heterogeneous data scoured from diverse sources make his metanalyses stronger. The thing that gave me the woollies was this line: “We start with […] The post Noisy, heterogeneous data scoured from diverse sources make his metanalyses stronger. appeared…

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Using Mister P to get population estimates from respondent driven sampling

October 31, 2017
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From one of our exams: A researcher at Columbia University’s School of Social Work wanted to estimate the prevalence of drug abuse problems among American Indians (Native Americans) living in New York City. From the Census, it was estimated that about 30,000 Indians live in the city, and the researcher had a budget to interview […] The post Using Mister P to get population estimates from respondent driven sampling appeared…

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An alternative to the superplot

October 28, 2017
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An alternative to the superplot

Kevin Brown writes: I came across the lexicon link to your ‘super plots’ posting today. In it, you plot the association between individual income (X) and republican voting (Y) for 3 states: one assumed to be poor, one middle income, and one wealthy. An alternative way of plotting this, what I call a ‘herd effects […] The post An alternative to the superplot appeared first on Statistical Modeling, Causal Inference,…

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My 2 talks in Seattle this Wed and Thurs: “The Statistical Crisis in Science” and “Bayesian Workflow”

October 23, 2017
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For the Data Science Seminar, Wed 25 Oct, 3:30pm in Physics and Astronomy Auditorium – A102: The Statistical Crisis in Science Top journals routinely publish ridiculous, scientifically implausible claims, justified based on “p < 0.05.” And this in turn calls into question all sorts of more plausible, but not necessarily true, claims, that are supported […] The post My 2 talks in Seattle this Wed and Thurs: “The Statistical Crisis…

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Freelance orphans: “33 comparisons, 4 are statistically significant: much more than the 1.65 that would be expected by chance alone, so what’s the problem??”

October 16, 2017
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From someone who would prefer to remain anonymous: As you may know, the relatively recent “orphan drug” laws allow (basically) companies that can prove an off-patent drug treats an otherwise untreatable illness, to obtain intellectual property protection for otherwise generic or dead drugs. This has led to a new business of trying large numbers of […] The post Freelance orphans: “33 comparisons, 4 are statistically significant: much more than the…

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