John Sakaluk

Those were good times, and pretty sure y'all were the only ones I was ever able to trade with for Gengars and Dragonites... I still have a pokemon-themed GB color + red cartridge that I'll play through every couple of years

Splitting the $ of a blue cartridge with Colin and Alain in grade 4...couldn't wait for my crack at the game.

So hard to choose, so I went with... 1) my fav. evolved starter, 2) my long-term/grind choice; and 3) I always had to have one, just because

YouTube video by Movies Déjà Vu Amadeus (1984) - Mozart Laughing Selection

Take care, as the "hahahahaha" {hahahahahavaan} is pronounced the Tom Hulce way:

www.youtube.com/watch?v=8PWb...

Quick, someone make the {hahahahavaan} package!

Paper on statistical power necessary for interaction effects
doi.org/10.1177/2515...

it immediately squashed it.

IT WAS/IS THE PERFECT EXAMPLE for when I return to teaching of why you still need to know your shit when deploying AI technologies (and how with oversight, they can offer tremendous value)!

...and so I got the AI to generate me a summary of what happened to share 😈

Friends, I just used an AI-tool in an R 📦 dev task; it found errors, and insisted it was a nothing-burger/probably dealing with an unrelated package; I reviewed what the AI-created functionality returned, and noticed a key, subtle omission; I pointed it to this problem; and >

adrftools: Estimating, Visualizing, and Testing Average Dose-Response Functions Facilitates estimating, visualizing, and testing average dose-response functions (ADRFs) for characterizing the causal effect of a continuous (i.e., non-discrete) treatment or exposure. Includes suppo...

I'm so excited to announce the first release of my newest #Rstats package, {adrftools}! This package facilitates estimation, visualization, and testing for the causal effect of a continuous (i.e., non-discrete) treatment.

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#statssky #episky #causalinference

Psych-y friends, anyone have any recommended readings for latest/greatest theories for labeling-related processes of interpersonal events and/or identities?

You should be freaking out about AI It works and it keeps getting better at an insane pace

"Even if I refuse to use AI for the supposed purposes of personal gratification that I get from reading and writing (manually), I’m not sure that’ll still seem worthwhile and enjoyable to me!

statsandsociety.substack.com/p/you-should...

For sure, and I'm lucky enough to develop in an area where the sensible "human heat-check" things to review/test are pretty obvious and straightforward.

But it took awhile--at least for me--to crest the psychological hump of figuring out my comfort with using it.

To wit: as a sabbatical stretch my brain activity, I am vibe-coding a mobile game (and as the author of that post described, "programming mostly in English").

I am an Okay R-programmer; I am a dog-shit C programmer. And yet, what I've cobbled together in a couple weeks is mind-numbing (for a noob)

are not really paying attention, or are swept up in some of the (understandable) first-order consequences (e.g., workload spiking through increased plagiarism cases) to stay connected to the rate of change with this tech

It took me so, so, so long to find--and I had to go outside of academe to a very code-savvy friend of a friend who works for a FANG company--what I felt was a 'balanced take' between the doomers and the [immediate] hype-monsters.

Have achieved some existential calm, but feels like most colleagues>

... then that's better "value" from me for the taxpayer and I ought to do it." So I've made my peace with involving it.

And while I'm somewhat sympathetic to the "intrinsic enjoyment" argument, as my uncle likes to quip, "If it was 'fun', it wouldn't be called 'work'".

I had this realization a few months back working on my R 📦 , where I'm increasingly using AI-bosted dev tools. I wondered whether I should be using them at all, or maintaining my "from scratch" approach. Landed on, "this [research] is my job, and if this tool helps me propel the software further >

Can you give an example of what such unit tests would look like? I might have too much "developer brain" at the moment, but I'm not intuiting what these tests would look like/offer beyond:
A) using a fully reproducible document type (e.g., .Qmd), and
B) rigorous unit testing in constituent pkgs

Model to Meaning: How to Interpret Statistical Models with R and Python Published in Journal of the American Statistical Association (Just accepted, 2026)

"Model to Meaning" just received a super generous review in JASA.

Check it out! (I'm blushing 😊)

Reminder: You can get the paper copy from CRC, and the full **free** version will remain online forever at marginaleffects.com

www.tandfonline.com/doi/full/10....

This approach is especially useful for #sexuality and #gender questions that use choose-all-that-apply options to better reflect people’s lived experiences (particularly in #trans research). I walk through the data-wrangling process with these examples variables!

📦: knickodem.github.io/CATAcode/

Using CATAcode for Choose-All-That-Apply Sexual Orientation and Gender Questions In mid-2025, I collected data from trans participants, and some of my survey questions were choose-all-that-apply. Since that time, Merrin and Nickodem (2025) released an R package, CATAcode, to he…

Started a blog! One of my first posts walks through how to prep your data to use the CATAcode #rpackage (with code + diagrams). With CATAcode, you can easily summarize and visualize responses from choose-all-that-apply questions:

catchingsplinters.wordpress.com/2026/01/27/u...

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I’ve been thinking about how to find R packages by functionality when you don’t already know the package name.

So over the holidays, Claude Code and I built The Warehouse: a functionality-first R package directory that helps you find packages by what they do.
rwarehouse.netlify.app

#rstats

So all colleges and universities will bring back the DEI stuff they cut when obeying in advance right...............................................................................................................................................right?

Noah's first foray into trans*-forward psychometrics is a banger! After a certain point, if your construct doesn't behave like you think it ought to, you start to reconsider foundational assumptions about the construct...

CATAcode: A Principled Approach for Coding Check-All-That-Apply Demographic Items - Gabriel J. Merrin, Kyle Nickodem, Nickholas Grant, Sitara M. Weerakoon, Melissa K. Holt, Dorothy L. Espelage, 2025 Accurately measuring, reporting, interpreting, and evaluating identity categories in social-science research is essential; however, check-all-that-apply (CATA) ...

📄: journals.sagepub.com/doi/10.1177/...

📦: cran.r-project.org/web/packages...

Speaking of #rstats, my buddy Joey Merrin and his colleagues recently published a paper in AMPPS/had an R package "CATAcode" accepted to CRAN.

Looks like a banger set of resources to navigate those finicky "choose-all-that-apply" (CATA) survey questions! Check it out!

WARN-D machine learning competition is live » Eiko Fried If you share one single thing of our team in 2026—on social media or per email with your colleagues—please let it be this machine learning competition. It was half a decade of work to get here, especi...

After 5 years of data collection, our WARN-D machine learning competition to forecast depression onset is now LIVE! We hope many of you will participate—we have incredibly rich data.

If you share a single thing of my lab this year, please make it this competition.

eiko-fried.com/warn-d-machi...

And thanks to @cq-n.bsky.social and Merissa Prine (not ob bsky: www.qnlovelab.com/team) for getting in on the fun with this release. We'd love for more collaborations of this kind!

dySEM: Dyadic Structural Equation Modeling Scripting of structural equation models via 'lavaan' for Dyadic Data Analysis, and helper functions for supplemental calculations, tabling, and model visualization.

I remain stoked on dySEM, and there's much more to come (hopefully)!

If you're a dyadic SEM user (or would-be user), get in touch! We'd love to know how to improve the software, what features you'd be keen to see, problems you are having, and ESPECIALLY if you're keen to contribute functionality.

Anyways. Lots to explore: new datasets, friendly/informative summary messages of scraped variables, tabling of latent correlations...

Next update will probably be less function-forward. @drmowinckels.io's #RPackageAdvent2025 thread has got me exited about website and documentation improvements.