Steen Flammild Harsted

Looks really good. Much use can come from this.

Maybe name the last function as_raw_typst()

Its only two letters more :)

You can help Ukraine and learn R at the same time. What's not to like?

Check out the workshops - seriously they look amazing

#RStats Dev Diary: Realization about this rendering technique: I'm not warping the object, I'm warping space to be non-euclidean!

"It is not the spoon that bends; it is only yourself."

#ThereIsNoSpoon

Thank you. I think it was actually this setting that I was looking for

Am I wrong, or does Positron default to the same ‘I do not care about reproducibility’ settings as RStudio?

For those who remember the good old Twitter days—here’s a throwback to a classic tip for settings in RStudio.

Can we get a similar guide for Positron?

@posit.co @hadley.nz
#rstats

Yes, I see that now.

I don't know how much of it is the prompting that Posit gives the Shiny Assistant, but the approach of Shiny Assistant was leagues better than what I got from gpt-5.

Ten minutes later… problem fixed.

It added error logs to my server.R, showed:

Warning: Error in %||%: could not find function "%||%"

…and that was it.

Shiny Assistant >>> ChatGPT-5

Seriously, check it out: gallery.shinyapps.io/assistant

#rstats

I just spent an entire day with ChatGPT-5 trying to fix a Shiny app that mysteriously crashed when deployed to our server.
We tried everything. Nothing worked. We even broke the app worse. Then spent hours slowly resurrecting it.

At 00:30 I suddenly remembered: Shiny Assistant by @posit.co

Ms 🪣 ?
Ms 💐 !

Loved this growing up 😄

sigh... I'm not allowed to play :/

For what it's worth, I dont think faces are as symmetrical as we tend to think they are :D

Hey. This is actually pretty cool.

In ellmer, is there any way to inspect the actual JSON schema that type_* creates? e.g. the opposite of type_from_schema()

type_array(
type_object(
x = type_boolean(),
y = type_string(),
z = type_number())) |>
type_to_schema() # <- what I need, but dont have

@posit.co
#rstats

That circle + angles is going to help me sooo much 🤩

I'm going with !!varname 🤞🙈

Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).

Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.

A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.

Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...

What an awesome update. 100% going to use this when making slides for lectures.

🤯

Beautifull.

Happy to say that 'mocapr' now supports import of joint center positions via .trc files from OpenCap.

github.com/steenharsted...

#rstats #mocap #opencap

I had more or less the same question a few days ago: bsky.app/profile/stee...

Got some good comments on that. Including one from @jennybryan.bsky.social

Amazing :D Never heard of this package before

Dear @posit.co,
I'm thinking about switching to Positron, but I heard the `here` package only works with RStudio projects.
I am afraid someone will set my computer on fire if I make the switch?
Please advise before the flames start. 🔥💻🧯

#rstats

I love hos Posit seems to be working non-stop on making packages that integrate LLMs into R and data-science workflows

I am looking to build a speech-to-speech chat-bot in Shiny.
Is this possible with the current ellmer and shiny-chat architecture?

Thanks

#rstats #shiny

Why is it good to force them back onto Western tankers?

Why is NF only third? I wonder if it is because he was not in the ruling party that had to execute the Brexit

Better repost this one...

Send her to Europe

YouTube video by PoliticsGirl One More Badass!

Yay AP called the NJ Governor Dem primary for our girl Mike Sherrill!!!
youtube.com/shorts/iUFWG...