Particularly pleased to see two points that I strongly advocated for included in the paper:
1/ Using the term "routinely collected data" rather than "real-world evidence"...
This was a great read. No idea how to get on top of this, perhaps pulling random people away from keyboards? Who knows!
techtrenches.substack.com/p/the-great-...
Putting myself out there a bit. Honest request from an open-source developer:
Can I please ask you to encourage people you know to stop with the "any updates on this?" discussion post? Every post like that genuinely makes me die inside a little bit.
I'll try to explain in this thread. 1/
yep - often mentioned in the stats group I work in. We don't get it, and seeing it has been a long time we have not got it, I start to think it is simply because we are not very smart when everyone else apparently gets it
It's bonkers that in academic science we spend hours obsessing over the wording of a paper, but often only one person has seen the code that produced the results! 2/N
I’ve seen situations in which people try to correct the scientific record and then critics act like that was superfluous or just not the right way to use one’s energy because “science is self-correcting.”
This just came to my mind
#uhoh Looks like OpenAI can take surveys for you… how are we going to stop this?? It’s currently only for “Pro Users” ($200/month) but eventually roll out.
Big threat to survey research
If one wanted to hire a professional #rstats#rshiny developer to work work with qualitative/text data in particular (so many involve a dashboard for search/semantic/sentiment analyses), do you have any recommendations of individuals or companies? (please repost)
🚨 **Challenging the Status Quo in Machine Learning: Are Class Imbalance Corrections Doing More Harm Than Good?** 🚨
In the world of machine learning, handling class imbalance has become almost second nature.
To be honest I think the control group is so poorly defined here that I put next to no value into the results. Then again I am biased against Nature as a journal going more for wow than quality. No serious journal puts the methods section at the end of a manuscript
Every week, I see a new study talking about this or that effect of GLP-1 receptor agonists like #ozempic. FINALLY, we have a study evaluating all the outcomes (good and bad) in one dataset. There are some... surprises. 🧵
On this day in 1862 in the city of Königsberg (now Kalinigrad, Russia) was born David Hilbert, most important mathematician of his generation. Panel below from Logicomix (www.logicomix.com), which remains one of my favorite books. Team Hilbert forever.
Go, shorty: New blog post! (How) should you interpret pre-post differences in a randomized study?
In which we introduce a new format, "reviewer notes" -- points that occasionally need to be made during the peer-review process.
www.the100.ci/2025/01/22/r...
If only more researchers realized that sometimes the right thing to do is to abandon an infeasible study, we could do things that are feasible, instead of wasting our (and reviewers'/readers') time trying to make sense of the senseless
Finally, another real advantage of causal inference is that you will better recognise situations where you cannot actually estimate the causal effect you are interested in, in any reliable way. So it is a good way to avoid doing things that are hopeless
𝚝𝚒𝚗𝚢𝚝𝚊𝚋𝚕𝚎 0.6.1 for #Rstats is out!
It's an ultra simple, super flexible, and 0-dependency package to draw beautiful tables in HTML, LaTeX, Typst, Word, PDF, and PNG.
And for those who ❤️ documentation, 𝚝𝚒𝚗𝚢𝚝𝚊𝚋𝚕𝚎 ships with a billion pages of tutorials:
vincentarelbundock.github.io/tinytable/
While we’re all putting #rstats opinions out there: base plot is better than ggplot because it’s default is so rubbish it forces people to think about design, whereas ggplot default is just about OK enough (but still far from good) to make people not bother.
To new users and followers: Here's a Shiny app showing the differences between three ways of including a continuous covariate in linear regression models.
Feel free to use it in your teaching or elsewhere! #rstats#datascience#statssky#stats#epi#episky
I made a Shiny app to showcase the differences between using a linear fit, a categorical fit and a (restricted cubic) spline fit under various data generating mechanisms.
The app is available at: apps.biostat.au.dk/stefan/splin...
Feel free to use it in your teaching #rstats #datascience #statssky