what's the recommended workflow for checking the accessibility of a #quarto website? currently i'm setting format: html: axe: output: document in _quarto.yml and checking every page visually and it's not particularly efficient #rstats

We have summer internships y'all! Come work at Posit on the PyData, tidymodels, shiny, or Connect teams: grnh.se/tigz810a3us. You will have an awesome time, learn a ton, and help advance our open source and pro tools 🧰 #rstats #pydata

Claude skills for reviewing manuscripts that I would appreciate: - stylistic advice for math writing (punctuating eqs, etc) - academic tropes (gaps, see quote) and linguistic oddities (gerund form) to avoid - structure of a good abstract/introduction - etc

Strength In Numbers is looking for a smart part-time survey research assistant (or a few) www.gelliottmorris.com/p/strength-i...

This might be the biggest job in (open) science. Cornell is creating a new non-profit organization to house @arxiv.bsky.social -- and hiring a new person to lead it. jobs.chronicle.com/job/37961678...

Grant Witness is hiring! We're seeking a full-time data scientist to join our team building data resources to support journalism, litigation, and activism protecting science, public health, and the rule of law. grant-witness.us/apply.html #rstats

once again learning the painful lesson that i need to pick a color scheme and set the correct page size before polishing my tikz figure 🥲

New on the arxiv: “Graphs are maximally expressive for higher-order interactions” arxiv.org/abs/2602.16937 We clarify central misconceptions in the recent literature on "higher-order networks". w/ @piratepeel.bsky.social , @manlius.bsky.social, and @thilogross.bsky.social Explainer 🧵: 1/N

Is there an #rstats package to visualize how many observations get dropped by each exclusion criteria? Looking for a nice visual way to summarize a sample

New paper! The Linear Representation Hypothesis is a powerful intuition for how language models work, but lacks formalization. We give a mathematical framework in which we can ask and answer a basic question: how many features can be stored under the hypothesis? 🧵 arxiv.org/abs/2602.11246

"Ten simple rules for teaching data science": arxiv.org/abs/2602.02874 A new preprint by @minecr.bsky.social and myself. We'd love any feedback!

Quick gist to pull census crosstabs: - age x sex x educ - age x sex x race - sex x race x educ to use during post-stratification gist.github.com/alexpghayes/...

Question for the pollsters: are there any public repos with census data/code to pull census data for re-weighting surveys with Mr. P?

At long last @zotero.org has an Android app!

Solidarity with everyone striking against ICE in MN and elsewhere If you'd like to do something: I'll match up to $100 in donations to any of the organizations listed on www.standwithminnesota.com

I'm looking forward to teaching a 4-hour short course on Bayesian sensitivity analysis methods at the American Causal Inference Conference (ACIC) 2026! Register here: sci-info.org/annual-meeti...

In a shocking turns of events, making a small change to my simulations did in fact fix everything

I just finished @gelliottmorris.com's delightful Strength in Numbers and I'm excited to read more about opinion research and polling Let me know if you have recommendations for followup reading!

which is the worse statistical sin, multiplying regression coefficients (mediation) or dividing regression coefficients (instrumental variables)

Keith and I strengthened our lower bounds for randomized experiments in the linear-in-means model to a general minimax result Updated results available at arxiv.org/abs/2410.10772

A new release of the mgcv #RStats 📦 is out on CRAN and Simon Wood (U Edinburgh) has added some significant new features despite the small bump in version number: 🌟 scasm() for estimating GAMs with shape constrained smooths. Can be used with any family & smoothness selection is via the EFS method

What are your favorite books/articles/resources about graphic design for academic posters and presentations?

Now I'm also looking for a research software engineer to implement a pile of research results to R packages loo, posterior, bayesplot, projpred, priorsense, brms or/and Python packages ArviZ, Bambi and Kulprit. Apply by email with no specific deadline (see contact info at users.aalto.fi/~ave/)

this thread nicely describes the epistemology of a decent portion of modern meta-science, and i think also explains why it lost steam

I missed that an expanded version of Philip Stark's "Pay No Attention to the Model Behind the Curtain" was published a few years back Needless to say it's very good and worth a read link.springer.com/10.1007/s000...

This may just be the best CS paper I’ve read this year. Just read the abstract and first para of the intro! The rest of the intro is really wild too, but very very good: dl.acm.org/doi/pdf/10.1...

Just read a referee report clearly generated by AI and I really hope journals start requiring Gen AI disclosures in referee reports

I was loving Claude Code... until I tried it with #rstats. Constant errors, wouldn't use the tidyverse even when asked, "optimized" functions were slower. Frustrated, I started a session just to teach R to Claude and summarize what it learned into a CLAUDE.md file gist.github.com/sj-io/3828d6...

nice guide to making github profiles (especially academic ones) legible to others!

Subhankar Bhadra, Michael Schweinberger Causal Inference Under Network Interference https://arxiv.org/abs/2508.06808

Also, we think people should stop using forensic meta-analytic techniques that have not been adequately vetted by experts in statistics. The p curve papers have very little statistical detail, and were published in psych journals. They did not get scrutiny appropriate to their popularity. 15/?

This workshop is going to be great fun, and I really look forward to meeting everyone! It would mean a lot to me if you signed up!

I'll be #JSM2025 from Sun Aug 3 - Thurs Aug 7 Excited to chat with folks! These days I'm thinking about: - peer effects - measurement error in networks - stochastic blockmodels and friends - causal inference on networks - semi-parametric mediation & transportability - #rstats

Technical writing is hard bcs "writing is thinking" but we often should tell our story not in the order we worked. Solution? I wrote a quick post on how @quarto.org 's embed shortcodes can reframe technical writing as reproducible evidence curation www.emilyriederer.com/post/quarto-... 🧵 (1/n)

Do folks know about A/B testing datasets where information about guardrail metrics is released alongside outcomes? #rstats #datascience #kaggle

boosting for the weekend crowd

Any tips and tricks for @typst.app <-> LaTeX translations? Pandoc is struggling with custom macros for notation and I'm weary of LLMs for technical writing (plus context window issues)

~~ making sense of academic statistics ~~ i wrote about the confusing relationship between statistics and data analysis, and also about how statistics relates to science #statistics #rstats #datascience www.alexpghayes.com/post/making-...

I've invested a lot into LaTeX in the last few years and didn't feel a strong desire to pivot, but I just tried @typst.app and I'm an immediate convert The compilation speed is so nice and it's so much easier to understand

The more I do multiverse data analysis, the more I find that conclusions vary dramatically with model specification. This makes me quite hesitant to trust empirical results using network models

Is there a go-to implementation of sparse SVD in #python? scipy.sparse.linalg.svds is much slower than the #rstats counterparts in {irlba} and {RSpectra} and I'm wondering if there are better options (I'm using the same data and CSR representations in both cases)

Hamilton, Tawn, Firth (2023) "The many routes to the ubiquitous Bradley-Terry model": arxiv.org/abs/2312.13619 Very cool! I've considered writing notes on how BT models can be motivated in myriad ways, with diff motivations leading to diff generalizations. This looks like a fantastic crack at that.

Evergreen

I'm looking for methods to visualize signed graphs with ~100 nodes and lots of negative edges So far the best I've come across is in {signnet} but I'm hoping I can find some other options github.com/schochastics...

link 📈🤖 Interpretable sensitivity analysis for the Baron-Kenny approach to mediation with unmeasured confounding (Zhang, Ding) Mediation analysis assesses the extent to which the exposure affects the outcome indirectly through a mediator and the extent to which it operates directly through other

Enjoying this conceptual paper on when/why predictive models can achieve causal goals

#dataviz #rstats Least squares by Springs: Here's a remarkable diagram, from 1932, illustrating a mechanical device to fit an exponential relation, y = A e^{-k x}, to data, here y= the milk yield of cows over x = 11 months. From: Gaines & Palfrey www.jstor.org/stable/1658643 ⬇️

So causalfusion.net and dagitty.net are great to check if controls C are sufficient to estimate the total effect of A on Y without needing to check backdoor paths yourself These tools can also algorithmically check if direct and indirect effects mediated by some M are identified!

Measuring the dynamical evolution of the United States lobbying network arxiv.org/abs/2503.11745

If you want to browse academic work without accidentally doom scrolling I cannot recommend this feed enough