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Archive of posts filed under the Public Health category.

Michael LaCour in 20 years

In case you were wondering what “Bruno” Lacour will be doing a couple decades from now . . . James Delaney pointed me to this CNN news article, “Connecticut’s strict gun law linked to large homicide drop” by Carina Storrs: The rate of gun-related murders fell sharply in the 10 years after Connecticut implemented a […]

Should you get the blood transfusion?

Gur Huberman writes: Apropos Ethics & Logistic Regression, the piece you wrote with Madigan: In late 2001 I [Gur] broke my femur trying to rollerblade with my daughter. (No IQ award for that.) I had surgery and my recovery was slow. Every time I tried to get on crutches I’d collapse and faint. Diagnosis: Anemia. […]

Stock, flow, and two smoking regressions

In a comment on our recent discussion of stock and flow, Tom Fiddaman writes: Here’s an egregious example of statistical stock-flow confusion that got published. Fiddaman is pointing to a post of his from 2011 discussing a paper that “examines the relationship between CO2 concentration and flooding in the US, and finds no significant impact.” […]

Can talk therapy halve the rate of cancer recurrence? How to think about the statistical significance of this finding? Is it just another example of the garden of forking paths?

James Coyne (who we last encountered in the sad story of Ellen Langer) writes: I’m writing to you now about another matter about which I hope you will offer an opinion. Here is a critique of a study, as well as the original study that claimed to find an effect of group psychotherapy on time […]

Social networks spread disease—but they also spread practices that reduce disease

I recently posted on the sister blog regarding a paper by Jon Zelner, James Trostle, Jason Goldstick, William Cevallos, James House, and Joseph Eisenberg, “Social Connectedness and Disease Transmission: Social Organization, Cohesion, Village Context, and Infection Risk in Rural Ecuador.” Zelner follows up: This made me think of my favorite figure from this paper, which […]

New research in tuberculosis mapping and control

Mapping and control. Or, as we would say, descriptive and causal inference. Jon Zelner informs os about two ongoing research projects: 1. TB Hotspot Mapping: Over the summer, I [Zelner] put together a really simple R package to do non-parametric disease mapping using the distance-based mapping approach developed by Caroline Jeffery and Al Ozonoff at […]

How is ethics like logistic regression?

Ethics decisions, like statistical inferences, are informative only if they’re not too easy or too hard. For the full story, read the whole thing.

Bayesian models, causal inference, and time-varying exposures

Mollie Wood writes: I am a doctoral student in clinical and population health research. My dissertation research is on prenatal medication exposure and neurodevelopmental outcomes in children, and I’ve encountered a difficult problem that I hope you might be able to advise me on. I am working on a problem in which my main exposure […]

“The Saturated Fat Studies: Set Up to Fail”

Russ Lyons points me to this recent magazine article by Martijn Katan and a research article, “Diet and Serum Cholesterol: Do zero correlations negate the relationship?” by David Jacobs, Joseph Anderson, and Henry Blackburn, and this video by Michael Greger. This is interesting stuff, especially as the ultimate truth is still very unknown. It’s good […]

“Academics should be made accountable for exaggerations in press releases about their own work”

Fernando Martel Garcia points me to this news article by Ben Goldacre: For anyone with medical training, mainstream media coverage of science can be an uncomfortable read. It is common to find correlational findings misrepresented as denoting causation, for example, or findings in animal studies confidently exaggerated to make claims about treatment for humans. But […]

Statistical Significance – Significant Problem?

John Carlin, who’s collaborated on some of my recent work on Type S and Type M errors, prepared this presentation for a clinical audience. It might be of interest to some of you. The ideas and some of the examples should be familiar to regular readers of this blog, but it could be useful to […]

Bayesian survival analysis with horseshoe priors—in Stan!

Tomi Peltola, Aki Havulinna, Veikko Salomaa, and Aki Vehtari write: This paper describes an application of Bayesian linear survival regression . . . We compare the Gaussian, Laplace and horseshoe shrinkage priors, and find that the last has the best predictive performance and shrinks strong predictors less than the others. . . . And here’s […]

How a clever analysis of health survey data became transformed into bogus feel-good medical advice

Jonathan Falk sends a message with the heading, “Garden of forking paths, p value abuse, questionable causality, you name it,” this link to an article in JAMA Internal Medicine, and the following remarks: Unfortunately, I can only see the first page of this article, but it seems to contain all the usual suspects. (a) Forking […]

“Epidemiology and Biostatistics: competitive or complementary?”

Mohammad Mansournia writes: I have a 20 minute lecture on “Epidemiology and Biostatistics: competitive or complementary?” at Tehran University of Medical Sciences in the next month. I should mention the difference between an epidemiologist and a biostatistician and their competitive or complementary roles in public health. I am wondering if you have any thoughts on […]

A New Year puzzle from Macartan Humphreys

Macartan writes: There is a lot of worry about publication and analysis bias in social science research. It seems results are much more likely to be published if they are statistically significant than if not which can lead to very misleading inferences. There is some hope that this problem can be partly addressed through analytic […]

Using statistics to make the world a better place?

In a recent discussion involving our frustration with crap research, Daniel Lakeland wrote: I [Lakeland] really do worry about a world in which social and institutional and similar effects keep us plugging away at a certain kind of cargo-cult science that produces lots of publishable papers and makes it easier to get funding for projects […]

The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation

All this discussion of plagiarism is leaving a bad taste in my mouth (or, I guess I should say, a bad feeling in my fingers, given that I’m expressing all this on the keyboard) so I wanted to close off the workweek with something more interesting. I happened to come across the above-titled paper by […]

Retrospective clinical trials?

Kelvin Leshabari writes: I am a young medical doctor in Africa who wondered if it is possible to have a retrospective designed randomised clinical trial and yet be sound valid in statistical sense. This is because to the best of my knowledge, the assumptions underlying RCT methodology include that data is obtained in a prospective […]

The history of MRP highlights some differences between political science and epidemiology

Responding to a comment from Thomas Lumley (who asked why MRP estimates often seem to appear without any standard errors), I wrote: In political science, MRP always seems accompanied by uncertainty estimates. However, when lots of things are being displayed at once, it’s not always easy to show uncertainty, and in many cases I simply […]

Debate over kidney transplant stats?

Dan Walter writes: A few years ago, in a post about Baysian statistics, you referred to a book that I wrote about a study on catheter ablation for atrial fibrillation: The Chorus of Ablationists I am writing a story on the transplant industry and am wondering about a widely cited article concerning the long term health effects of […]