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Archive of posts filed under the Public Health category.

The Pandora Principle in statistics — and its malign converse, the ostrich

The Pandora Principle is that once you’ve considered a possible interaction or bias or confounder, you can’t un-think it. The malign converse is when people realize this and then design their studies to avoid putting themselves in a position where they have to consider some potentially important factor. For example, suppose you’re considering some policy […]

“This finding did not reach statistical sig­nificance, but it indicates a 94.6% prob­ability that statins were responsible for the symptoms.”

Charles Jackson writes: The attached item from JAMA, which I came across in my doctor’s waiting room, contains the statements: Nineteen of 203 patients treated with statins and 10 of 217 patients treated with placebo met the study definition of myalgia (9.4% vs 4.6%. P = .054). This finding did not reach statistical sig­nificance, but […]

It’s hard to know what to say about an observational comparison that doesn’t control for key differences between treatment and control groups, chili pepper edition

Jonathan Falk points to this article and writes: Thoughts? I would have liked to have seen the data matched on age, rather than simply using age in a Cox regression, since I suspect that’s what really going on here. The non-chili eaters were much older, and I suspect that the failure to interact age, or […]

“Explaining recent mortality trends among younger and middle-aged White Americans”

Kevin Lewis sends along this paper by Ryan Masters, Andrea Tilstra, and Daniel Simon, who write: Recent research has suggested that increases in mortality among middle-aged US Whites are being driven by suicides and poisonings from alcohol and drug use. Increases in these ‘despair’ deaths have been argued to reflect a cohort-based epidemic of pain […]

How to design future studies of systemic exercise intolerance disease (chronic fatigue syndrome)?

Someone named Ramsey writes on behalf of a self-managed support community of 100+ systemic exercise intolerance disease (SEID) patients. He read my recent article on the topic and had a question regarding the following excerpt: For conditions like S.E.I.D., then, the better approach may be to gather data from people suffering “in the wild,” combining […]

Hey—here are some tools in R and Stan to designing more effective clinical trials! How cool is that?

In statistical work, design and data analysis are often considered separately. Sometimes we do all sorts of modeling and planning in the design stage, only to analyze data using simple comparisons. Other times, we design our studies casually, even thoughtlessly, and then try to salvage what we can using elaborate data analyses. It would be […]

Clinical trials are broken. Here’s why.

Someone emailed me with some thoughts on systemic exertion intolerance disease, in particular, controversies regarding the Pace trial which evaluated psychological interventions for this condition or, should I say, set of conditions. I responded as follows: At one point I had the thought of doing a big investigative project on this, formally interviewing a bunch […]

Further criticism of social scientists and journalists jumping to conclusions based on mortality trends

[cat picture] So. We’ve been having some discussion regarding reports of the purported increase in mortality rates among middle-aged white people in America. The news media have mostly spun a simple narrative of struggling working-class whites, but there’s more to the story. Some people have pointed me to some contributions from various sources: In “The […]

You can read two versions of this review essay on systemic exertion intolerance disease (chronic fatigue syndrome)

Julie Rehmeyer wrote a book, “Through the Shadowlands: A Science Writer’s Odyssey into an Illness Science Doesn’t Understand,” and my review appeared in the online New Yorker, much shortened and edited, and given the title, “A memoir of chronic fatigue illustrates the failures of medical research.” My original was titled, “Systemic exertion intolerance disease: The […]

Maternal death rate problems in North Carolina

Somebody named Jerrod writes: I though you might find this article [“Black moms die in childbirth 3 times as often as white moms. Except in North Carolina,” by Julia Belluz] interesting as it relates to some of your interests in health data and combines it with bad analysis and framing. My beef with the article: […]

Bayesian, but not Bayesian enough

Will Moir writes: This short New York Times article on a study published in BMJ might be of interest to you and your blog community, both in terms of how the media reports science and also the use of bayesian vs frequentist statistics in the study itself. Here is the short summary from the news […]

Problems with the jargon “statistically significant” and “clinically significant”

Someone writes: After listening to your EconTalk episode a few weeks ago, I have a question about interpreting treatment effect magnitudes, effect sizes, SDs, etc. I studied Econ/Math undergrad and worked at a social science research institution in health policy as a research assistant, so I have a good amount of background. At the institution […]

Where’d the $2500 come from?

Brad Buchsbaum writes: Sometimes I read the New York Times “Well” articles on science and health. It’s a mixed bag, sometimes it’s quite good and sometimes not. I came across this yesterday: What’s the Value of Exercise? $2,500 For people still struggling to make time for exercise, a new study offers a strong incentive: You’ll […]

“Bombshell” statistical evidence for research misconduct, and what to do about it?

Someone pointed me to this post by Nick Brown discussing a recent article by John Carlisle regarding scientific misconduct. Here’s Brown: [Carlisle] claims that he has found statistical evidence that a surprisingly high proportion of randomised controlled trials (RCTs) contain data patterns that cannot have arisen by chance. . . . the implication is that […]

More graphs of mortality trends

Corinne Riddell writes: In late March you released a series of plots visualizing mortality rates over time by race and gender. For almost a year now, we’ve been working on a similar project and have compiled all of our findings into an R shiny web app here, with a preprint of our first manuscript here. […]

Come to Seattle to work with us on Stan!

Our colleague Jon Wakefield in the Department of Biostatistics at the University of Washington is interested in supervising a 2-year postdoc through this training program. We’re interested in finding someone who would with Jon and another faculty member (who is assigned on the basis of interests) on exciting projects in spatio-temporal modeling and the environmental […]

All the things we have to do that we don’t really need to do: The social cost of junk science

I’ve been thinking a lot about junk science lately. Some people have said it’s counterproductive or rude of me to keep talking about the same few examples (actually I think we have about 15 or so examples that come up again and again), so let me just speak generically about the sort of scientific claim […]

How to interpret “p = .06” in situations where you really really want the treatment to work?

We’ve spent a lot of time during the past few years discussing the difficulty of interpreting “p less than .05” results from noisy studies. Standard practice is to just take the point estimate and confidence interval, but this is in general wrong in that it overestimates effect size (type M error) and can get the […]

Riddle me this

[cat picture] Paul Alper writes: From Susan Perry’s article based on Paul Hacker’s BMJ article: In 2015, the University of Colorado had to shut down its nonprofit Global Energy Balance Network after the organization was exposed as being essentially a “scientific” front for its funder, Coca-Cola. The University of Colorado School of Medicine returned […]

The statistical crisis in science: How is it relevant to clinical neuropsychology?

[cat picture] Hilde Geurts and I write: There is currently increased attention to the statistical (and replication) crisis in science. Biomedicine and social psychology have been at the heart of this crisis, but similar problems are evident in a wide range of fields. We discuss three examples of replication challenges from the field of social […]