Peter Damgaard

dplyr 1.2.0 dplyr 1.2.0 fills in some important gaps in dplyr's API: we've added a new complement to `filter()` focused on dropping rows, and we've expanded the `case_when()` family with three new recoding and re...

dplyr 1.2.0 is out now and we are SO excited!

- `filter_out()` for dropping rows

- `recode_values()`, `replace_values()`, and `replace_when()` that join `case_when()` as a complete family of recoding/replacing tools

These are huge quality of life wins for #rstats!

tidyverse.org/blog/2026/02...

Is meat consumption becoming political? @willemboterman.bsky.social & @eelcoharteveld.bsky.social examine Dutch surveys showing meat eating aligns with right-wing ideology & climate scepticism. Read OPEN ACCESS: buff.ly/HU5Mdec

@polstudiesassoc.bsky.social #polsky #polsci #FoodPolitics

We’re organizing a workshop at Aarhus University. Please share and consider submitting!

🗓️ 13–14 April 2026 | 📝 Deadline: Mon, 16 Feb 2026 (extended abstract) — junior scholars prioritized

🎤 Keynotes: @stefwalter.bsky.social (Univ. of Zurich) & @hhuang.bsky.social (Ohio State)

Survey experiments have become a popular methodology among social scientists. Has it been effective?

In POQ, Rauf et al. study the efficacy of 100 survey experiments. Their results show that a majority of hypotheses were not supported.

Read now: doi.org/10.1093/poq/...

Here comes another aviation analogy.

I sincerely hope that these types of tools will be used to help us do _better_ research first and foremost.

I fear instead it will be used to help us do _more_ research _faster_.

The magic of autopilot is that it helps pilots fly better, not more.

Will you incorporate LLMs and AI prompting into the course in the future? No. Why won’t you incorporate LLMs and AI prompting into the course? These tools are useful for coding (see this for my personal take on this). However, they’re only useful if you know what you’re doing first. If you skip the learning-the-process-of-writing-code step and just copy/paste output from ChatGPT, you will not learn. You cannot learn. You cannot improve. You will not understand the code.

In that post, it warns that you cannot use it as a beginner: …to use Databot effectively and safely, you still need the skills of a data scientist: background and domain knowledge, data analysis expertise, and coding ability. There is no LLM-based shortcut to those skills. You cannot LLM your way into domain knowledge, data analysis expertise, or coding ability. The only way to gain domain knowledge, data analysis expertise, and coding ability is to struggle. To get errors. To google those errors. To look over the documentation. To copy/paste your own code and adapt it for different purposes. To explore messy datasets. To struggle to clean those datasets. To spend an hour looking for a missing comma. This isn’t a form of programming hazing, like “I had to walk to school uphill both ways in the snow and now you must too.” It’s the actual process of learning and growing and developing and improving. You’ve gotta struggle.

This Tumblr post puts it well (it’s about art specifically, but it applies to coding and data analysis too): Contrary to popular belief the biggest beginner’s roadblock to art isn’t even technical skill it’s frustration tolerance, especially in the age of social media. It hurts and the frustration is endless but you must build the frustration tolerance equivalent to a roach’s capacity to survive a nuclear explosion. That’s how you build on the technical skill. Throw that “won’t even start because I’m afraid it won’t be perfect” shit out the window. Just do it. Just start. Good luck. (The original post has disappeared, but here’s a reblog.) It’s hard, but struggling is the only way to learn anything.

You might not enjoy code as much as Williams does (or I do), but there’s still value in maintaining codings skills as you improve and learn more. You don’t want your skills to atrophy. As I discuss here, when I do use LLMs for coding-related tasks, I purposely throw as much friction into the process as possible: To avoid falling into over-reliance on LLM-assisted code help, I add as much friction into my workflow as possible. I only use GitHub Copilot and Claude in the browser, not through the chat sidebar in Positron or Visual Studio Code. I treat the code it generates like random answers from StackOverflow or blog posts and generally rewrite it completely. I disable the inline LLM-based auto complete in text editors. For routine tasks like generating {roxygen2} documentation scaffolding for functions, I use the {chores} package, which requires a bunch of pointing and clicking to use. Even though I use Positron, I purposely do not use either Positron Assistant or Databot. I have them disabled. So in the end, for pedagogical reasons, I don’t foresee me incorporating LLMs into this class. I’m pedagogically opposed to it. I’m facing all sorts of external pressure to do it, but I’m resisting. You’ve got to learn first.

Some closing thoughts for my students this semester on LLMs and learning #rstats datavizf25.classes.andrewheiss.com/news/2025-12...

At will? Whose will? Removing independent agency heads is part of a broader assault on a nonpartisan government

I was going to just share an excerpt of this great @donmoyn.bsky.social piece, but there are too many excerpts worth sharing. Just read the whole thing. If you care about governance, democracy, and the rule of law, these issues are crucial. open.substack.com/pub/donmoyni...

I consider this piece on information spillover/information equivalence a must-read for survey experimentalists. It's addresses a key limitation for many survey experiments (especially the hypothetical scenario/vignette type) www.cambridge.org/core/journal...

Designing Information Provision Experiments (March 2023) - Information provision experiments allow researchers to test economic theories and answer policy-relevant questions by varying the information set available to respondents. We survey the...

Treatment can also be (new) information focusing on effects on belief updating and downstream outcomes. See also "information provision experiments" in econ lit www.aeaweb.org/articles?id=...

Today I published a replication outlining concerns with "Instrumentally Inclusive" by Turnbull-Dugarte and López Ortega (2024, APSR).

I document seemingly idiosyncratic and ad hoc choices made by the authors that create a pattern of statistically significant results consistent with their theory.

🚨 SynthNet is out 🚨
Researchers propose new constructs and measures faster than anyone can track. We (@anniria.bsky.social @ruben.the100.ci) built a search engine to check what already exists and help identify redundancies; indexing 74,000 scales from ~31,500 instruments in APA PsycTests. 🧵1/3

Selective reporting

I recently had a similar issue and ended up using a solution combing geom_step with a histogram as detailed by @kjhealy.co here: kieranhealy.org/blog/archive...

📄 New WP version out - full overhaul!

The Politics of Evidence Selection (w/ @jesperasring.bsky.social )

Comments welcome!

🔗 osf.io/preprints/so...

Interesting new study on the elusive connection between organizational performance and user satisfaction

After a huge post-election flip in economic perceptions, I thought Democrats and Republicans might be lying to pollsters to send a partisan message — but I was wrong!

New in the Journal of Experimental Political Science (open access): doi.org/10.1017/XPS....

Title: A Justification for 80% Power Abstract: Cohen’s heuristic reason for choosing 80% power (balancing Type I and TypeII errors) conveniently arrives at approximately the same number as an approachwhere one maximizes the marginal gain in power per standard error reduction. Ihave yet to see someone point this out, and this is interesting because it providesa non-arbitrary justification for 80% power.

a derivation of the result

I think this is kind of neat and I don't think anyone else has noticed it (I've looked and I can't find anyone who has) osf.io/preprints/so...

Maybe I should back off "justification" language, but it's at least a remarkable coincidence. I still think someone else *must* have noticed it...

When there is a random way to do something, there is a less random way that is better but requires more thought. In this case, regression models that make no sense don't belong in a multiverse analysis. An inferential regression without a causal justification is like an opinion without reasons.

If your random seed is 42 I will come to your office and set your computer on fire🔥 Figuratively. More likely you'll get a stern talking to.

We need to have a conversation about random seeds. Don't use 42.
blog.genesmindsmachines.com/p/if-your-ra...

Postdoctoral Fellow in Political Science (3-4 years) (288628) | University of Oslo Job title: Postdoctoral Fellow in Political Science (3-4 years) (288628), Employer: University of Oslo, Deadline: Monday, November 17, 2025

We are hiring PhDs and postdocs to work on the ERC project GETGOV, where I am the PI.

We will investigate governing elites since 1789. I am sure that it will be a lot of fun and result in great research!

Postdocs: www.jobbnorge.no/en/available...

PhDs: www.jobbnorge.no/en/available...

👀 this new meta-analysis on edutainment by @bardiarahmani.bsky.social, Montano, @dylanwgroves.bsky.social, and Green

doi.org/10.1017/bpp....

377 ests in 77 exps: edutainment moves attitudes, norms, beliefs 📊
Effects persist ⏳
Many reasonable theories about effect heterogeneity are not supported 😇

Currently in FirstView: In “Balancing Precision and Retention in Experimental Design,” @gustavodiaz.org and Erin Rossiter study how experimental design choices can increase precision when estimating treatment effects. Specifically, they examine block-randomized and pre-post designs.

great story, this chart RULES

osf.io/preprints/ps...
Preprint: Jan Pfänder and Hugo Mercier "The rational impression account of trust in science"

Modernising administrations: making positive change happen 1. Teaser for Modernising administrations: making positive change happen 1.

"citizens, businesses and public administrations in the EU could save an estimated €64.2 billion a year from better performing administrations?"

Glad to see first parts of our EUPACK work on the cost of underperformance in public admin being released.

reform-support.ec.europa.eu/public-admin...

The Making of a Ghetto: Place-Based Policies, Labeling, and Impacts on Neighborhoods and Individuals ROCKWOOL Foundation

Interesting paper on the effect of Denmark's Ghetto Plan
www.rfberlin.com/network-pape...

Do high workloads force bureaucrats to discriminate?

In a published paper at the @thejop.bsky.social, I challenge the dominant explanation of discrimination in public service delivery. Surprisingly, I find that bureaucrats are able to handle substantial workloads without discriminating.

ggplot2 4.0.0 A new major version of ggplot2 has been released on CRAN. Find out what is new here.

I am beyond excited to announce that ggplot2 4.0.0 has just landed on CRAN.

It's not every day we have a new major #ggplot2 release but it is a fitting 18 year birthday present for the package.

Get an overview of the release in this blog post and be on the lookout for more in-depth posts #rstats

Earnings expectations of “First-in Family” university students and their role for major choice How do students’ earnings expectations differ by being the first in their family to attend university (FiF) and how do they affect field of study choi…

Interesting paper by ‪@alisonandrew.bsky.social and ‪@abicadams.bsky.social‬ on first-in family university students, very relevant for risk-aversion debate www.sciencedirect.com/science/arti...

Forskere skulle gøre deres projekt »spiseligt for erhvervet« for at få adgang til data om dyrevelfærd Den tidligere landbrugsstyrelse har givet ejerskab over data indsamlet af offentligt ansatte på de danske slagterier til Landbrug & Fødevarer. Det kan være et brud på offentlighedsloven og brud på EU-...

Landbruget har alt, alt for megen magt i Danmark. Som i: mafialignende magt.

Her er et gavelink til en helt gak historie om at lade landbruget eje offentlige kontroldata. Det svarer til at give alle data om lungekræft til tobaksfabrikanterne og lade dem bestemme, hvilke forskere, der får adgang.