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Frank Harrell @f2harrell.bsky.social · 1d

Yongxi Long and colleagues have written an excellent post about when and when not to worry about the proportional odds assumption: discourse.datamethods.org/t/when-and-w... #StatsSky #EpiSky #Statistics #RStats

When and why (not) to worry about the PO assumption

Aim We wrote an article (Long, Wiegers, Jacobs, Steyerberg, & Van Zwet, 2025) about the proportional odds (PO) assumption in the analysis of ordinal outcomes. we use various examples from neurological...

discourse.datamethods.org

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Frank Harrell @f2harrell.bsky.social · 1d

That's largely true. The biggest problem is the amount of medical practice that has not been researched.

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Frank Harrell @f2harrell.bsky.social · 2d

Anyone who gets to work with Aki is very lucky …

Aki Vehtari @avehtari.bsky.social · 2d

I'm looking for a doctoral student with Bayesian background to work on Bayesian workflow and cross-validation (see my publication list users.aalto.fi/~ave/publica... for my recent work) at Aalto University.

Apply through the ELLIS PhD program (dl October 31) ellis.eu/news/ellis-p...

ELLIS PhD Program: Call for Applications 2025

The ELLIS mission is to create a diverse European network that promotes research excellence and advances breakthroughs in AI, as well as a pan-European PhD program to educate the next generation of AI...

ellis.eu

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Frank Harrell @f2harrell.bsky.social · 2d

The extremely problematic use of change scores is so poorly understood by researchers that it’s almost sickening. Most don’t even understand what is needed for the subtraction operator to work. hbiostat.org/bbr/change

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Frank Harrell @f2harrell.bsky.social · 4d

An excellent argument. One related way I try to get course managers’ attention is to quote the cost of SPSS licenses to students once they leave the comfort of the university site license. The cost is obsene, for a product that does far less than R, & LLM can even help students learn to program R

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Reposted by Frank Harrell

David Colquhoun @davidcolquhoun.bsky.social · 4d

Good grief ICE!

Mike Galsworthy @mikegalsworthy.bsky.social · 4d

History repeats.

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Reposted by Frank Harrell

Andrew Heiss @andrew.heiss.phd · 5d

If you've ever wanted to learn how to make beautiful websites with #QuartoPub and #rstats , check out this workshop I'm giving in a couple weeks! It'll be a blast (and we're covering Quarto's brand new _brand dot yaml system!)

Statistical Horizons @stathorizons.bsky.social · 20d

Learn to create and publish a professional, data-focused website in “Create an Online Presence with Quarto Websites” on October 16-17, with @andrew.heiss.phd‬! Discover how to use #Quarto to build a variety of websites like personal portfolios, research compendiums, and interactive dashboards.

Quarto Websites | Online Seminar | Code Horizons

This online course taught by Andrew Heiss, Ph.D., teaches you how to use Quarto to build a variety of data-focused websites.

codehorizons.com

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Reposted by Frank Harrell

Peter Tennant @pwgtennant.bsky.social · 5d

"Uncooperative statistician": the term used (typically by a senior clinician) to describe a well-trained and knowledgeable statistician who refuses to conduct flawed or fraudulent research.

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Frank Harrell @f2harrell.bsky.social · 8d

Flexible Goal-Drive Bayesian Design - video of presentation is now available at www.fharrell.com/talk/gdesign/ #Statistics #StatsSky #bayes #rct

Goal-Driven Flexible Bayesian Design – Statistical Thinking

The majority of clinicals trials that are successfully launched end with equivocal results, with confidence intervals that are too wide to allow drawing a conclusion other than “the money was spent”. ...

www.fharrell.com

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Frank Harrell @f2harrell.bsky.social · 8d

In addition an equally important requirement is that the study is actually designed, i.e., that the investigators cared enough about the question to get funding for prospective data collection, QC, and unbiased outcome evaluation.

Reposted by Frank Harrell

R Works @rworks.bsky.social · 8d

August 2025's Top 40 picks are out, highlighting excellent #RStats packages from Differential Privacy to Toxicology to Causal Inference.

This marks 1 year of Top 40 posts since we started R Works! 🎉

Check out the post here: rworks.dev/posts/august...

August 2025 Top 40 New CRAN Packages – R Works

Here are my picks for the best from the ninety-seven new packages that landed on CRAN in August, organized in eighteen categories: Causal Inference, Data, Differential Privacy, Ecology, Environmental ...

rworks.dev

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Frank Harrell @f2harrell.bsky.social · 8d

After decades as a teacher experiencing such issues, my conclusion is to have a single pre-course personal laptop R setup help session and put an absolute requirement that setup be completed a week before class starts.

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Reposted by Frank Harrell

Richard Riley (R²) @richarddriley.bsky.social · 8d

Giving a talk today which anyone can watch online: 1pm - 2pm
"The Importance of Sample Size for the Development and Evaluation of Clinical Prediction Models"
- intended for a broad audience (anyone doing or using prediction model research)
imperial-ac-uk.zoom.us/webinar/regi...

Welcome! You are invited to join a webinar: Research Methods Academy: Seminar - The Importance of Sample Size for the Development and Evaluation of Clinical Prediction Models. After registering, you w...

Led by Professor Richard Riley Join this Online Seminar on clinical prediction models estimate individual risk for outcomes from disease. Many studies lack rigorous design; this session will focus o...

imperial-ac-uk.zoom.us

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Frank Harrell @f2harrell.bsky.social · 8d

But I’d rather see such laziness than have researchers say “consuming soy lowers the risk of breast cancer” etc. And I’d like to see the modest “predicts” used more often, supplemented with “further understanding of pathways is required for a causal conclusion about the predictor”.

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Frank Harrell @f2harrell.bsky.social · 9d

Thanks. It may be interesting to study the meaning of estimands when not conditioning on a strong factor when the estimator is non-collapsible as with binary Y.

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Frank Harrell @f2harrell.bsky.social · 9d

It would be interesting to see an example where that is reasonable. I know this situation exists but can’t believe it would be very common. We also have the age variable even though it raises a privacy issue, hence age is sometimes truncated at 80 or so to prevent re-identification.

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Frank Harrell @f2harrell.bsky.social · 9d

If X is predictive of outcome and X was used in probability sampling but X was not stored in the dataset, isn’t that a major design flaw?

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Frank Harrell @f2harrell.bsky.social · 9d

But see discourse.datamethods.org/t/illogic-of...

Illogic of Weighting While Estimating Model Parameters

Consider a situation where some types of subjects are over- or under-sampled from a population where the sampling probabilities are known. For example, to increase efficiency we might sample a greate...

discourse.datamethods.org

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Frank Harrell @f2harrell.bsky.social · 9d

fharrell.com/post/marg

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Frank Harrell @f2harrell.bsky.social · 9d

That’s the main reference, a simple demonstration of how unadjusted estimates are ill-defined and easily manipulated by subject inclusion criteria even with complete homogeneity of effects.

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Reposted by Frank Harrell

aliciablackgirl.bsky.social @aliciablackgirl.bsky.social · 10d

The main reason Revenge Dump's in office again and not in prison where he belongs is cos Mitch McConnell violated his oath of office and didn't lead the Senate to vote for impeachment. Thanks Mitch that decision will haunt you to your grave and as long as there's still recorded history afterwards.

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Reposted by Frank Harrell

Julia M. Rohrer @dingdingpeng.the100.ci · 11d

Psychologists are also definitely guilty of confusing change with treatment response, which is why I wrote about it here:

www.the100.ci/2025/01/22/r...

Reviewer notes: In a randomized experiment, the pre-post differences are not effect estimates

Reviewer notes are a new short format with brief explanations of basic ideas that might come in handy during (for example) the peer-review process. They are a great way to keep Julia from writing 10,0...

www.the100.ci

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Frank Harrell @f2harrell.bsky.social · 10d

It’s not just confounding; when the outcome is binary or time-to-event, failure to condition on important prognostic factors results in ill-defined effect estimates even with zero confounding.

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Frank Harrell @f2harrell.bsky.social · 10d

The fact that most meta-analyses use unadjusted estimates casts doubt on the meta-analysis field.

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Reposted by Frank Harrell

Julia M. Rohrer @dingdingpeng.the100.ci · 11d

“Doing research is a choice, and unless you’re involved in some urgent project—curing a disease or winning a war or righting some injustice or raising living standards or whatever—or some interesting project—baseball statistics or the theory of random walks or whatever—you shouldn’t do it.”

Andrew Gelman et al. @statmodeling.bsky.social · 14d

More on the decline and fall of Steven Levitt
statmodeling.stat.columbia.edu/2025/09/24/m...

More on the decline and fall of Steven Levitt | Statistical Modeling, Causal Inference, and Social Science

statmodeling.stat.columbia.edu

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