Robin Blythe

Robin Blythe

@rbly.bsky.social

Health economist dabbling in biostats and clinical informatics. https://orcid.org/0000-0002-3643-4332

711 followers530 following2.7K posts

Sign of a great talk: 80% of people coming up to you after congratulate you on a wonderful presentation. The remaining 20% tell you to eat shit and die, and that you will set back the profession by decades.

Robin Blythe@rbly.bsky.social

Will be speaking on Monday at the Asia launch of the Lancet Commission on Oral Health in Singapore. Come watch me tell a bunch of dentists that most dental care is just provider induced demand! www.ndcs.com.sg/events/healt...

You know you've effectively been stats-pilled as an economist when you convince yourself that stochastic utility models are the most elegant explanation of human behaviour #econsky

Robin Blythe@rbly.bsky.social

Fun thread. I've long preferred the position that a utility function is just an latent data generating process that can only be approximated by viewing its contextual outputs (a spin on revealed preferences theory, basically). "Irrationality" labels are just cope from badly guessing at the true DGP.

Robin Blythe reposted

Give this social media employee from the Dutch National Institute for Public Health and the Environment a raise! Vaccine-skeptic, in response to information about yearly flu-vaccinations: "Up your a***" RIVM: "Vaccinations are typically injected into the upper arm."

Work-issue laptop #rstats workflow: open file explorer. Wait 3 minutes for it to crash and restart. Open RStudio. Wait 5 minutes to load. Load rstanarm. Wait 5 minutes to load. Run brms code. Wait 10 minutes to compile. Wait 30 minutes for sampling. Home laptop workflow: everything done in 3 min 🫨

Smoking-gun evidence of socioeconomic factors affecting dental general anaesthesia rates at an industrial level, and am onto my 8th desk reject because the methods are 'too simple' (comparing two logistic models + g-computation). How do I sex this thing up? Do I call it AI? Causal?

Reading Breiman again and wondering whether this dichotomy is still valid. His take homes are excellent: 1) focus on the problem and the data; 2) if you are after the DGP, predictive accuracy matters most. But the point of much applied work is to propose and test a mechanism. (1/4) #statsky #episky

Ben Recht@beenwrekt.bsky.social

Subtweeting yesterday’s AI discourse, I wrote about Breiman’s Two Cultures paper and what we want from our forecasting models.

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G-computation, a feature of DGP papers, is effectively a prediction task: predict Y while manipulating X, works for any model. Likewise, the obsession with "explain ability" (it's always just Shapley) in data science suggests peering inside the black box is at least highly alluring.(3)

Anyway, maybe Breiman's paper worked as intended. It was 25 years ago and stats has evolved a lot. Many statisticians are happy to do prediction work (my thesis was on predicting clinical deterioration) and thinking about a DGP is a nice philosophical anchor. Or maybe I'm a moron. Quite plausible!

Reading Breiman again and wondering whether this dichotomy is still valid. His take homes are excellent: 1) focus on the problem and the data; 2) if you are after the DGP, predictive accuracy matters most. But the point of much applied work is to propose and test a mechanism. (1/4) #statsky #episky

Ben Recht@beenwrekt.bsky.social

Subtweeting yesterday’s AI discourse, I wrote about Breiman’s Two Cultures paper and what we want from our forecasting models.

Many newer papers take this tack: using domain knowledge, propose a DGP. Apply evidence (the data) for/against it. Use predictive accuracy to validate the model. Few applied researchers start with the arrogant belief their model is correct anymore (except causal inference 😉). (2)

Mentoring med students projects in #psych and it's all just paper mills looking at "clinical correlates", all the time. Same pipeline: pick y. Collect hundreds of "correlates". Run them all in univariate models. Build a frankenmodel with all the p<0.05 ones. Report p<0.05. What the fuck is this?

To be clear: the students are doing what the supervisors are saying to do. I don't blame them. Said supervisor in one case has hundreds of papers like this and is on the Elsevier "World's Top Scientists" list. We trust our mental health with these people lol

The hardest part of working on oral health grants is that you realise most journals do not give the remotest shit about dental outcomes lol. It's tough out there

It's not just your intuition; a lot of papers about LLMs are cowboy science. Important work showing that this extends to clinical trials. #medsky

Gary Collins@gscollins.bsky.social

NEW PAPER in the @bmj.com: “Reporting completeness of clinical trials evaluating large language model interventions in medicine: systematic review” Underreporting of LLM specific methodological details, protocols, data, code, and harms Read the paper here www.bmj.com/content/395/...

Submitted to @plosone.org in March 2025. Took until Jan 2026 to get first round of reviews, I resubmit, and it goes out for review again. Now the editor is unreachable, paper's reassigned, and I have no idea what the status is. Do I cut my losses? It's infuriating. #academia

Nice study that I don't fully agree with, but makes a lot of important points about the shit show that is clinical data and the folly that is assuming that clinical prediction models work. Many of the same data issues also in clinical target trial emulation. #medsky #episky

sciencedirect.comsciencedirect.com

Implementation scientists when you ask whether their frameworks or results can be quantified, tested or in any way validated #medsky ;)

My brother's nurse at the flu shot appointment: "The most common question I get these days is whether there's AI in the vaccine"

Are there any good reasons for people to take photos of slides sharing yet-unpublished research at conferences? I've now witnessed two cases of research theft from colleagues via this behaviour and can no longer assume people who photo your slides do so in good faith. Too uncharitable?

Another nice blog post (not just because I agree with it!) that reinforces a particularly tough pill for many scientists to swallow: there are lots of really strange assumptions that do the heavy lifting when we seek to call our process "exploratory", often at the expense of theoretical grounding!

Vera Wilde@handle.invalid

Causal discovery. What is it good for? I've criticized the Glymour–Spirtes Tetrad tradition before; NOTEARS is its younger cousin. I ran a simulation showing if you rescale one variable, the "causes" change. Causality first! Analyses second. wildetruth.substack.com/p/no-tears-f...

Maybe a hot take, but IMO the best thing about propensity scoring is that it makes clear how absurdly difficult it is to reduce complex patients/clinician+patient interactions down to a handful of variables. It virtually always obviates some missing and/or irreducible context. #statsky #episky

Given that coding is basically a mapping from human-to-computer readable language, it really does seem like the natural evolution is to abstract away the human-readable part (ie, code), making it a smooth transition from human lay language straight to binary.

Complaining about people not knowing how to code seems a little weird when I guarantee most people have absolutely no clue what, for example, glmer() is actually doing under the hood

Weirdly, this was the post that spurred this particular line of thought

William B. Fuckley@opinionhaver.bsky.social

If you drink enough of the codewater you can enter latent space and pry the vectors loose from their embedding. They are shiny, like gems.

How should national expanded carrier screening programs for rare diseases be structured? Evidence from Singapore. First time running a discrete choice experiment and got to do some neat policy analyses. Shoutout to the MVP {logitr} (and, as usual, {ggplot2}) #econsky rdcu.be/6TvA8v58DKpa

Singapore: Beware of scams! Here's an anti-scam PSA you'll get multiple times a day! Also Singapore: all private companies are allowed to use marketing tactics undifferentiable from how scammers operate. We have no plans to regulate this.

This was fun. Would have also squeezed Disco Elysium in for a top 10, and this doesn't include what is probably like >8000 hours playing Super Smash Bros and Melee at friends houses

lastpositivist.bsky.social@lastpositivist.bsky.social

I did this meme thing to say the 9 games that express my soul (it says its down but you can just do it here: my9games.net/en/edit) and these are it. They express my soul.

Applied #statsky and health #econsky friends: any good methods-focused conferences you recommend? I am feeling a little deflated by how little my peers in health economics care about methods. Extra points if there is a focus on Bayes, prediction, and decision theory. I'm in Singapore but can travel!

Just got a review request from a Frontiers journal that was so intensely personalised to my prior publications (in other journals) that it borders on stalking. A somewhat creepy experience.

I would like to announce I finally watched the Odyssey and quite enjoyed it, and require no further Discourse at this time. Thank you

This is why it's incredible to me that the US govt is not taking more charge of how these companies interface with their allies. It's using OpenAI and Anthropic in an almost mercantilist way, at least rein in their stupidest behaviours! I guess you need actual experts in charge for that, though.

William B. Fuckley@opinionhaver.bsky.social

it's a minor detail, but it really seems like a pretty strong signal of one of two things: -pretty staggering incompetence, not something that's a good sign in a company that thinks it's building god -not giving a shit *at all* about something serious enough that the Prime Minister got involved

New #healtheconomics #preprint in which we propose a proportionality argument for evaluation of clinical AI: that if the model leads to changes in the way patients are treated, then it must meet the evidentiary standards of that treatment.

papers.ssrn.com<p><span>Towards Rigorous Economic Evidence for Clinical AI</span></p><p><span>Clinical artificial intelligence (AI) joins a long list of technologies that promise to improve healthcare, but lack the evidence that it leads to valu

A lot of bullshit research gets a pass under "exploratory" work. Fishing for p-values is just exploring how to cook the books for your next study. What are some good, actually principled, exploratory stats/Econ methods? #statsky

To me there is a fundamental problem when you start with the data and retrofit your theory. You can just as easily be demonstrating collider bias as finding a true association. IMO, true exploratory research should be blind to Y and based on first principles.

It is SO EASY to specify mo() for an ordinal variable in brms that I don't think I can go back to treating them as continuous or dummy vars. Even splines are super easy. Next on my wishlist is that mi() integrates cleanly with mo() and s() 😍 #rstats

All fields tend to some degree to confuse normative statements for scientific rigour, but I don't think I can tolerate reading any more "Planetary health" papers

Just as the AI hype types are (poorly) reinventing statistics, the anti-AI crew are (poorly) reinventing decision theory and economics. Please just open a book.

We must pace the frontier of logistic regression. It is too powerful, and the risk to humanity of incorrect interpretations of odds ratios is an existential threat #statsky #ai

Been teaching grad students a bit lately, and hoo boy, nothing makes you question education quality as much as your complete lack of confidence in your own knowledge.