Vincent Arel-Bundock

Whoa—my book is up for pre-order! Model to meaning: How to interpret Statistical & ML Models in #RStats and #PyData The book presents an ultra-simple and powerful workflow to make sense of ± any model you fit Note: The web version stays free forever. tinyurl.com/4fk56fc8

@__gsteck__ Looks fantastic!

We refactored Bambi's interpret module, extending its features to align more with @VincentAB R's marginaleffects.

This is infuriating. #NullEffectsMatter

@KyleLHandley @bechhof You can treat maintainers with respect and get the ***free*** stuff you want. Win-win.

@KyleLHandley @bechhof Instead of throwing insulting complaints up on social media ("anyone who picks up a textbook"), perhaps you could ask the maintainer (me) it we could convert the error into a warning. I am always happy to engage with users, listen to feedback, and fix (potentially) bad decisions.

So just to complain about open source R a bit. Somebody decided the "marginaleffects" package should not work with PPML models because of FE uncertainty that definitely apply in some model prediction (but NOT my application). So they just broke the whole thing instead. Why can't users just make their own mistakes? github.com/vincentarelbun… "car" package will still do what I want anyway, but not I have rewrite my teaching code, my slides, and my solutions for students. The problem of fixed effects being concentrated out of PPML and conditional logit models is well know. STATA will give you a warning on this and anyone that can be bothered to pick up a textbook can know this. Weird unilateral decisions by package managers probably breaking tons of code for past 7 months.

Say I wanted ~9k USD to buy out the teaching time of a prof (a brilliant coauthor of mine) so he can work on creating a validated ground truth dataset for a challenging data extraction and labelling task that current public LLMs (e.g. GPT5) have not yet saturated. Who do I pitch?

Discover how rare it can be to uncover meaningful effects in political science research in this week’s episode of Not Another Politics Podcast. Listen here: har.rs/493JVn3

@robma1982 routledge.com/Model-to-Meani…

@VincentAB the link seems broken

Whoa—my book is up for pre-order! Model to meaning: How to interpret Statistical & ML Models in #RStats and #PyData The book presents an ultra-simple and powerful workflow to make sense of ± any model you fit Note: The web version stays free forever. tinyurl.com/4fk56fc8

@xuyiqing I've been playing with your ideas for Step 2 and found a super cute 1-liner. Using the `transform` argument of the `comparisons` function, we can spline dydx immediately, instead of using cumbersome bins. Not sure this is actually useful, but it's too cool not to post!

It works for simple cases, but both steps may have some drawbacks, e.g., binning works not as well at boundaries. Thx a lot for digging into it!

@VincentAB Thought a bit more. CME estimation with cont. X typically involves: (1) Get signals for partial effect/CATE given covariates. (2) Reduce to 1D along X (e.g., binning, kernel, spline). Your implementation uses GAM numerically for (1) and binning for (2).

@xuyiqing Oh yeah, doubly-robust is the good stuff! I also really like the part of your paper about dimensionality and regularization bias. A very clear and concise treatment. Good work!

Thx, Vincent. Agreed! I didn’t know about this fn in marginaleffects -- super useful! Our point on the critique’s *implementation* of GAM stands. Moreover, accommodating additional Z and regularization bias remain challenging. Doubly-robust estimators generally perform better.

@xuyiqing Interesting paper! Thanks for posting. IIUC, your main concern with the GAM approach is that it targets the wrong estimand. If so, I feel that your criticism of the approach is kind of unfair, given that it's easy to target CME w/ GAM. See this notebook: arelbundock.com/hmx_simonsohn.…

1/ Recently, Professor Uri Simonsohn critiqued Hainmueller, Mummolo & Xu (2019), arguing that the proposed methods fail to recover the conditional marginal effect (CME): datacolada.org/121 We appreciate the critique and offer this response: arxiv.org/pdf/2502.05717 🧵

@LeoBaccini That's all fine but, fundamentally, I'm not convinced that the president is actually looking for policy concessions. And I worry that spending more CAD in these areas will embolden further extortion attempts.

Paradoxically, a trade war between bordering countries is at risk of worsening security border issues or to create problems that do not currently exist. And I leave the economic costs out in this thread. 11/11

The US declared to impose 25% tariffs on imports from Canada and Mexico (effective from Tuesday). Canada has retaliated with 25% tariffs on US imports. A trade war between these two major trading partners brings no benefits to their economies and their citizens. A thread: 1/11

@robertwiblin Ungated early version at OSF: doi.org/10.31219/osf.i…

@robertwiblin You may be interested in our recent paper, where we show there is public support for buy-outs like the one you recommend. See Journal of Politics, Buy-in for Buyouts: Attitudes Toward Compensation for Reform journals.uchicago.edu/doi/10.1086/73…

Buy and close the mink farms. astralcodexten.com/p/h5n1-much-mo…

@ToniSoto_Vigo Yes! @stephenjwild tracked down the original quote behind this paraphrase of Dawid (1985).

"A parameter is just a resting stone on the road to prediction (Philip Dawid)" Via @VincentAB

Struggling with complex statistical results? Watch the first hour of @VincentAB’s "Interpreting and Communicating Statistical Results with R" on YouTube, and join the full seminar March 27-28 to learn an advanced toolkit in #Rstats! youtu.be/wKvFAs6-fNA

@noahzucker @Princeton @PUPolitics @LSEIRDept That's amazing news. Congratulations!!

Thrilled to share that I will be joining @Princeton @PUPolitics as an Assistant Professor later this year. It'll be difficult leaving amazing colleagues @LSEIRDept, but I'm looking forward to these next steps! 🐅

@kaw_355 There is a very easy and well-documented strategy to revert back to {kableExtra} if you want. I do not recommend doing that in new projects, but it can be useful for backward compatibility in old code. See here: #version-2.0.0-kableextra-and-tinytable" target="_blank" rel="nofollow noopener">modelsummary.com/man/modelsumma…

@kaw_355 The reason {modelsummary} changed in version 2.0.0 is that we used to rely on {kableExtra} to draw tables. That package is no longer actively developed, and it has many bugs that go unfixed. The package now relies on {tinytable}, and this will be stable in the future 1/2

modelsummaryの変更まじで困るよなぁ

@ohtanilson @mixingale That said, I strongly recommend you use the new table format. There are very good reasons to switch to tinytable, I think. But for backward compatibility with old code, the options linked above are useful!

@VincentAB @mixingale Thx!

modelsummaryのv2.0以降でoutput = latex_tabularが機能しなくなってる？？？