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Archive of posts filed under the Public Health category.

Performing design calculations (type M and type S errors) on a routine basis?

Somebody writes writes: I am conducting a survival analysis (median follow up ~10 years) of subjects who enrolled on a prospective, non-randomized clinical trial for newly diagnosed multiple myeloma. The data were originally collected for research purposes and specifically to determine PFS and OS of the investigational regimen versus historic controls. The trial has been […]

A political sociological course on statistics for high school students

Ben Frisch writes: I am designing a semester long non-AP Statistics course for high school juniors and seniors. I am wondering if you had some advice for the design of my class. My currentthinking for the design of the class includes: 0) Brief introduction to R/ R Studio and descriptive statistics and data sheet structure. […]

Aahhhhh, young people!

Amusingly statistically illiterate headline from Slate: “Apple Notices That Basically Half the Population Menstruates.” Ummmm, let’s do a quick calculation: 50 – 12 = 38. If you assume the average woman lives to be 80, then the proportion of the population who is menstruating is approximately .52*38/80 = .247. 25% is hardly “basically half”! But […]

“Soylent 1.5” < black beans and yoghurt

Mark Palko quotes Justin Fox: On Monday, software engineer Rob Rhinehart published an account of his new life without alternating electrical current — which he has undertaken because generating that current “produces 32 percent of all greenhouse gases, more than any other economic sector.” Connection to the power grid isn’t all Rhinehart has given up. […]

Macartan Humphreys on the Worm Wars

My Columbia political science colleague shares “What Has Been Learned from the Deworming Replications: A Nonpartisan View”: Last month there was another battle in a dispute between economists and epidemiologists over the merits of mass deworming.1 In brief, economists claim there is clear evidence that cheap deworming interventions have large effects on welfare via increased […]

Classifying causes of death using “verbal autopsies”

Tyler McCormick sent along this paper, “Probabilistic Cause-of-death Assignment using Verbal Autopsies,” coauthored with Zehang Li, Clara Calvert, Amelia Crampin, Kathleen Kahn, and Samuel Clark: In areas without complete-coverage civil registration and vital statistics systems there is uncertainty about even the most basic demographic indicators. In such areas the majority of deaths occur outside hospitals […]

Pro Publica’s new Surgeon Scorecards

Skyler Johnson writes: You should definitely weigh in on this… Pro Publica created “Surgeon Scorecards” based upon risk adjusted surgery compilation rates. They used hierarchical modeling via the lmer package in R. For detailed methodology, click the methodology “how we calculated complications” link, then atop that next page click on the detailed methodology to download […]

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 […]