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Archive of posts filed under the Public Health category.

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 […]

Boo! Who’s afraid of availability bias?

Just in time for Halloween: I came across this 2-minute video by Brian Zikmund-Fisher, a professor of Health Behavior and Health Education at the University of Michigan, and I took a look because I was curious what he had to say. The video is called “Why aren’t we more scared of measles?” and has the […]

People used to send me ugly graphs, now I get these things

Antonio Rinaldi points me to this journal article which reports: We found a sinusoidal pattern in CMM [cutaneous malignant melanoma] risk by season of birth (P = 0.006). . . . Adjusted odds ratios for CMM by season of birth were 1.21 [95% confidence interval (CI), 1.05–1.39; P = 0.008] for spring, 1.07 (95% CI, […]

One of the worst infographics ever, but people don’t care?

This post is by Phil Price. Perhaps prompted by the ALS Ice Bucket Challenge, this infographic has been making the rounds: I think this is one of the worst I have ever seen. I don’t know where it came from, so I can’t give credit/blame where it’s due. Let’s put aside the numbers themselves – […]

The health policy innovation center: how best to move from pilot studies to large-scale practice?

A colleague pointed me to this news article regarding evaluation of new health plans: The Affordable Care Act would fund a new research outfit evocatively named the Innovation Center to discover how to most effectively deliver health care, with $10 billion to spend over a decade. But now that the center has gotten started, many […]

The Ben Geen case: Did a naive interpretation of a cluster of cases send an innocent nurse to prison until 2035?

In a paper called “Rarity of Respiratory Arrest,” Richard Gill writes: Statistical analysis of monthly rates of events in around 20 hospitals and over a period of about 10 years shows that respiratory arrest, though about five times less frequent than cardio-respiratory arrest, is a common occurrence in the Emergency Department of a typical smaller […]

“The Europeans and Australians were too eager to believe in renal denervation”

As you can see, I’m having a competition with myself for the most boring title ever. The story, though, is not boring. Paul Alper writes: I just came across this in the NYT. Here is the NEJM article itself: And here is the editorial in the NEJM: The gist is that on the basis of […]

“P.S. Is anyone working on hierarchical survival models?”

Someone who wishes to remain anonymous writes: I’m working on building a predictive model (not causal) of the onset of diabetes mellitus using electronic medical records from a semi-panel of HMO patients. The dependent variable is blood glucose level. The unit of analysis is the patient visit to a network doctor or hospitalization in a […]

As if we needed another example of lying with statistics and not issuing a correction: bike-share injuries

This post is by Phil Price A Washington Post article says “In the first study of its kind, researchers from Washington State University and elsewhere found  a 14 percent greater risk of head injuries to cyclists associated with cities that have bike share programs. In fact, when they compared raw head injury data for cyclists […]

Spring forward, fall back, drop dead?

Antonio Rinaldi points me to a press release describing a recent paper by Amneet Sandhu, Milan Seth, and Hitinder Gurm, where I got the above graphs (sorry about the resolution, that’s the best I could do). Here’s the press release: Data from the largest study of its kind in the U.S. reveal a 25 percent […]

Hurricanes vs. Himmicanes

The story’s on the sister blog and I quote liberally from Jeremy Freese, who wrote: The authors have issued a statement that argues against some criticisms of their study that others have offered. These are irrelevant to the above observations, as I [Freese] am taking everything about the measurement and model specification at their word–my […]