Malcolm 朝精 Barrett

Recoding a `score` column using a Likert scale lookup table and a new `recode_values()` function in dplyr

If you find yourself still reaching for `dplyr::recode(x, !!!values)` or `plyr::mapvalues()`, then I think you'll like `recode_values()`!

We are looking for some community feedback on 3 new dplyr functions!

- replace_when()
- recode_values()
- replace_values()

New tools for recoding (think, lookup tables!) and replacing (think, replace `-99` with `NA` in `col`) in the tidyverse - I'm pretty excited about these!

This week on What's New in R, we're featuring:

✅ Tips for quickly opening Positron projects on macOS by Andrew Heiss
✅ A look at a customized version of RStudio with AI capabilities
✅ Cara Thompson’s talk on creating interactive data visualizations in R

Read the issue: buff.ly/z0Tuob3

#rstats

This image depicts a line graph showing cardiovascular mortality rates in the United States from 1933 to 2023, alongside key advancements in medicine, surgery, and public health. The y-axis represents age-standardized death rates from cardiovascular disease, ranging from 0 to 600. The x-axis represents years from 1933 to 2023. The graph starts at around 600 deaths per 100,000 people in 1933 and trends downward sharply over the decades, indicating a significant decline in mortality rates. Key advancements are marked along the timeline, including the introduction of the first heart-lung machine in 1953, the first cardiac CT scan in 1977, and the first 3D-printed heart models in 2012. Footnote information states that data begins in 1933 when all U.S. states started reporting cardiovascular mortality rates, sourced from the National Center for Heart Statistics in 2020 and the CDC Wonder in 2025. The chart is published by Saloni Dattani at Our World in Data.

New article by me!

Cardiovascular disease mortality rates have declined by around three-quarters since 1950, but we rarely hear about it.

I explore some of the reasons behind the decline.
ourworldindata.org/cardiovascul...

Writing lecture notes in Quarto during missile attack in Kyiv underground

#AcademicLife in Ukraine: preparing for lectures at night during a massive missile attack on Kyiv in an overcrowded underground station
#EconSky #UkrainianView #RStats

If you haven’t gotten into marginaleffects yet, this may be your chance. Learning about it has been quite transformative for how I think about statistical modeling 🪄

❗️Our next workshop will be on August 14, 6 pm CEST, on marginaleffects package by
@vincentab.bsky.social !
Register or sponsor a student by donating to support Ukraine!
Details: bit.ly/3wBeY4S
Please share! #AcademicSky #EconSky #RStats

Firing the BLS Commissioner — the wonk in charge of the statisticians who track economic reality — is an authoritarian four alarm fire.

It will also backfire: You can't bend economic reality, but you can break the trust of markets. And biased data yields worse policy.

The good news is, now that we've gotten rid of "data" the analytical value of vibes has skyrocketed

That’s it I’m firing R because my results weren’t significant

Title slide for our talk at useR entitled "Plot Tiwst:Adding interactivity to the elegance of ggplot2 with ggiraph"

The virtual #user2025 event takes place today — and our talk "Plot Twist: Adding Interactivity to the Elegance of ggplot2 with ggiraph" airs is lined up next! 🎥

#rstats #ggiraph #ggplot2 #dataviz

"WASHINGTON, D.C. (August 1, 2025) – The Corporation for Public Broadcasting (CPB) announced today that it will begin an orderly wind-down of its operations"

cpb.org/pressroom/Co...

That’s what I’m thinking. Personally, I had a wooden bat with nails in it so same vibe

Also I thought you were holding a metal baseball bat and I thought that’s a pretty cool way to take a defense picture

Congrats, Dr. Carr!

YouTube video by useR! Conference A first look at Positron - Julia Silge

My @user-conf.bsky.social virtual talk, a first look at Positron for #rstats folks, posted while I was asleep 😴 but you can catch it here:
youtu.be/aKSrptGegeo?...

YouTube video by useR! Conference A first look at Positron - Julia Silge

It's the virtual day for useR! Some of the talks are already available, including this one: I always enjoy @juliasilge.com explaining things so if you are curious about the Positron IDE (it's out of beta now!), this is for you:
www.youtube.com/watch?v=aKSr... #rstats

Hello #dataBS! I'm facilitating a new free @dslc.io Advanced #RStats adv-r.hadley.nz cohort soon! It's been 5+ years since I read this excellent book by @hadley.nz, so I'm giving it a re-read. Let's learn to embrace {{ tidy evaluation }}, purrr::reduce() repetition, and count S/R #OOP systems!

A promotional image for "Introduction to Machine Learning in R with tidymodels" at posit conf (2025). The image features Simon Couch, from Posit, smiling outdoors in a headshot. The text "Atlanta" and "Sept. 16-18" are also visible, alongside abstract cubes in orange, green, and blue.

A promotional image for "Causal Inference in R" at posit conf (2025). The image features two individuals: Malcolm Barrett from Stanford and Lucy D'Agostino McGowan from Wake Forest University. Malcolm Barrett is shown in a headshot with a blurred background, and Lucy D'Agostino McGowan is shown smiling with a blackboard in the background. The text "Atlanta" and "Sept. 16-18" are also visible, along with abstract cubes in orange, green, and blue.

A promotional image for "Getting More Out of Feature Engineering and Tuning for Machine Learning" at posit conf (2025). The image features Max Kuhn and Emil Hvitfeldt, both from Posit. Max Kuhn is shown in a headshot with a blurred background, and Emil Hvitfeldt is shown smiling with plants in the background. The text "Atlanta" and "Sept. 16-18" are also visible, along with abstract cubes in orange, green, and blue.

Check out our Modeling & ML with #RStats workshops at posit::conf!

🔢 Intro to ML w/ tidymodels @simonpcouch.com
🏗️ Feature Engineering & Tuning @topepo.bsky.social @emilhvitfeldt.bsky.social
↔️ Causal Inference @malcolmbarrett.malco.io @lucystats.bsky.social

Learn more: pos.it/conf-2025-workshops

“We used ANOVA, where our research question went through dimension reduction”

The big show

Going outside but shaking my head the whole time so people know I don’t agree with what’s going on

We've released 4 new chapters of Applied Machine Learning for Tabular Data.

Includes: Bayesian optimization, feature selection, model comparisons, classification metrics, calibration, #rstats computing sections, and more

blog.aml4td.org/posts/2025-0...

i need someone to do this to my brain

A @sherrirose.bsky.social classic!

Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies Abstract. Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of

Gentlest #TMLE intro I know is this one:

academic.oup.com/aje/article-...

Yeah but a common support group sounds very positive

Shhh don’t scare them away Paul!!!!

There should probably be a support group for comforting and being comforted that the theory behind TMLE is legitimately hard. It is!

Throw in “something something clever covariate” and you’re there