iiinova — where your digital self keeps evolving

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Magnus Johansson @pgmj.bsky.social · 28/09/2026

Our commentary "A Revolution in Search of an Estimand: On the Idionomic Proposal of Hayes et al. (2026)" is now available as a preprint: osf.io/preprints/ps... With @rpsychologist.com, @matti.vuorre.com, and Nils Hentati Isacsson.

osf.io

OSF

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Aki Vehtari @avehtari.bsky.social · 13/08/2026

All four books I've co-authored are freely available online for non-commercial use: - Bayesian Workflow at avehtari.github.io/Bayesian-Wor... Links to other three books are in the quoted post 👇 (too many books to fit in one post!)

avehtari.github.io

Bayesian Workflow book: Website – Bayesian Workflow book

Website for the Bayesian Workflow book by Gelman, Vehtari, McElreath, et al. — case studies, code, and exercises in R and Stan.

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Peer Review Congress #PRC11 Coming 2029! @peerreviewcongress.bsky.social · 10/04/2026

The ERROR project recruits independent experts to recheck social sciences papers’ data, statistics, methodology, code; now the project plans to publish the reviews in a new peer-reviewed journal. science.org/content/arti... @dalmeet.bsky.social @science.org #reproducibility

science.org

Offering scientists cash to spot errors in published papers doesn’t work

The ERROR project tried enticing reviewers with payments. Now, it’s launching a journal—and promising papers as rewards

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 07/04/2026

I would have preferred to have the "draw the rest of the owl" meme on the cover, but this will do. Seems like it is on schedule, and we'll leave some typos so you know we didn't write it with AI.

cover of the book "Bayesian Workflow" by Gelman, Vehtari, et al. Coming out later this year, in the summer probably.

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Paul Smaldino @psmaldino.bsky.social · 02/04/2026

I've been thinking a lot about the foundations of cultural evolutionary theory. While there's been a lot of work on transmission mechanisms, there has been far less work on cultural *selection*. Here's a new working paper presenting a taxonomy of cultural selection processes. osf.io/preprints/so...

Title page for working paper: "The Varieties of Cultural Selection"

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 02/04/2026

how I feel when open science initiatives choose to publish in Nature

Batman breaking a firearm and saying, "This is the journal of the enemy. We do not need it. We will not use it."

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Matti Vuorre @matti.vuorre.com · 01/04/2026

To lead in open science efforts, we must engage in open science practices. These papers reporting on the reproducibility et al of science projects aren't even accessible. At least one of the commentaries was also closed access. This is a huge lost opportunity and sets a bad example to all.

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Rich May @richiemay.bsky.social · 29/12/2025

Excellent chapter-by-chapter discussion of Skinner’s oft-dismissed, but seldom read, Verbal Behavior podcasts.apple.com/gb/podcast/c...

podcasts.apple.com

Chapter 1: A Functional Analysis of Verbal Behavior

Podcast Episode · Dialogues on Verbal Behavior · 18/09/2024 · 1h 49m

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Rich May @richiemay.bsky.social · 28/12/2025

post a perfect album from the 90s that isn't nirvana, pearl jam, soundgarden, or alice in chains

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Tim Kaiser @tkaiser.science · 12/12/2025

🔥 New viewpoint paper accepted at Journal of Psychopathology and Clinical Science! I propose a behavioral conceptualization of personality functioning (PF) that reframes the construct in terms of learned self-related repertoires rather than inferred inner structures.

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Tim Kaiser @tkaiser.science · 11/12/2025

Right on time for the upcoming holidays, and an upcoming paper, this arrived 🙂

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Riccardo Fusaroli @fusaroli.eurosky.social · 15/10/2025

The takeaway: Turn-taking isn't a single, monolithic trait that reflects social competence. It’s a multicomponential skill that emerges from the interplay of individual differences, moment-to-moment predictions, and interpersonal adjustments—all shaped by social context. 8/

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Riccardo Fusaroli @fusaroli.eurosky.social · 15/10/2025

Conversational turn-taking feels effortless, but it's a complex dance. We find social context—who you're talking to and what you're talking about—fundamentally changes conversational dynamics in both autistic & TD children. 1/ onlinelibrary.wiley.com/doi/10.1111/... w @chrismmcox.bsky.social

onlinelibrary.wiley.com

Social Context Matters for Turn‐Taking Dynamics: A Comparative Study of Autistic and Typically Developing Children

Engaging in fluent conversation is a surprisingly complex task that requires interlocutors to promptly respond to each other in a way that is appropriate to the social context. In this study, we dise...

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Jamie Cummins @jamiecummins.bsky.social · 18/09/2025

Can large language models stand in for human participants? Many social scientists seem to think so, and are already using "silicon samples" in research. One problem: depending on the analytic decisions made, you can basically get these samples to show any effect you want. THREAD 🧵

arxiv.org

The threat of analytic flexibility in using large language models to simulate human data: A call to attention

Social scientists are now using large language models to create "silicon samples" - synthetic datasets intended to stand in for human respondents, aimed at revolutionising human subjects research. How...

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Felix W. Moll @mollfw.bsky.social · 11/09/2025

New paper on precise tool use learning in carrion crows @currentbiology.bsky.social. We show that—like New Caledonian crows—expert carrion crows pay close attention to the working end of their tool, suggesting tool integration into their peripersonal space. 🧵 & vids! 👇 www.cell.com/current-biol...

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Julia M. Rohrer @dingdingpeng.the100.ci · 25/08/2025

Ever stared at a table of regression coefficients & wondered what you're doing with your life? Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social) Preprint: doi.org/10.31234/osf... Website: j-rohrer.github.io/marginal-psy...

Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities

Abstract
Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).

Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.

A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals).

Illustrated are
1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals
2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and
3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.

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Rich May @richiemay.bsky.social · 23/08/2025

For a coffee person on a budget (me!), there is no better combo….

Cafelat Robot lever press espresso machine and a Commandante C40 hand grinder

36g of Espresso in an espresso cup with a Dachshund illustration

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Mike Frank @mcxfrank.bsky.social · 01/07/2025

Experimentology is out today!!! A group of us wrote a free online textbook for experimental methods, available at experimentology.io - the idea was to integrate open science into all aspects of the experimental workflow from planning to design, analysis, and writing.

Experimentology cover: title and curves for distributions.

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easystats @easystats.github.io · 24/06/2025

Unlock hidden patterns in longitudinal data! 🚀 Our new vignette shows how to use brms & easystats to perform Growth Mixture Models, identify unique developmental trajectories, and visualize & interpret your findings with ease. #rstats #brms #easystats easystats.github.io/modelbased/a...

easystats.github.io

An Introduction to Growth Mixture Models with brms and easystats

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Tom Wallis @tsawallis.bsky.social · 16/04/2025

It's bonkers that in academic science we spend hours obsessing over the wording of a paper, but often only one person has seen the code that produced the results! 2/N

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Rich May @richiemay.bsky.social · 18/04/2025

B.F Skinner from the paper, “How to discover what you have to say” pmc.ncbi.nlm.nih.gov/articles/PMC...

Quote from BF Skinner about writing and self-discovery. It states that immediate consequences like surprising yourself with new ideas, clarifying confusing points, and enjoying your own writing are effective in discovering your authentic voice.

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Vincent Arel-Bundock @vincentab.bsky.social · 10/04/2025

📚😅🎉 Yay!! I just submitted the complete manuscript of my upcoming book to the publisher! Learn to easily and clearly interpret (almost) any stats model w/ R or Python. Simple ideas, consistent workflow, powerful tools, detailed case studies. Read it for free @ marginaleffects.com #RStats #PyData

Model to Meaning: How to interpret statistical models with marginaleffects for R and Python

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Riccardo Fusaroli @fusaroli.eurosky.social · 28/02/2025

I was recommending my students @jonathantemplin.com 's awesome course recordings (jonathantemplin.com/teaching/) to get more in-depth discussion of stan tips and psychometrics models and I discovered there's a new 2024 version. house chores will be more fun for a while.

jonathantemplin.com

Teaching

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Dr Lucy Foulkes @lucyfoulkes.bsky.social · 10/02/2025

Important new evidence published today: large-scale DofE trial (N=12,166) found that two universal MH awareness interventions, in secondary schools, led to an *increase* in emotional symptoms at long term (9-12 month) follow up tinyurl.com/4ffday8y Thread below /1

Department for Education. Effectiveness of school mental health awareness interventions
Universal approaches in English secondary schools
February 2025

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Nick Clark 💹 @njclark.bsky.social · 04/02/2025

Another video in my series on applied time series and forecasting with the {mvgam} #rstats 📦. This one introduces State Space hierarchical GAMs and GPs for tackling multivariate series youtu.be/2POK_FVwCHk?...

youtu.be

Time series in R and Stan using the mvgam package: hierarchical GAMs

YouTube video by Nicholas Clark

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Rich May @richiemay.bsky.social · 28/01/2025

Behaviour goes where reinforcement flows. Choice of task driven by relative success rate. Three preregistered experiments with young kids. Open version here jlnrd.github.io/Publications...

jlnrd.github.io

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ERROR @error.reviews · 20/01/2025

New report! Hehman et al. (2018) "Disproportionate Use of Lethal Force in Policing Is Associated With Regional Racial Biases". Based on the review by @conjugateprior.org, we find a Major Error that affects a core conclusion. We recommend the authors seek a correction. error.reviews/reviews/hehm...

error.reviews

Hehman et al. (2018)

ERROR is a bug bounty program for science to systematically detect and report errors in academic publications

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Mark Rubin @markrubin.bsky.social · 17/01/2025

UK universities might misattribute changes in their rankings to their institutional strategies when random fluctuations in the ranking system are a more likely explanation. Preprint: osf.io/preprints/ps... BSky author: @tvpollet.bsky.social #UKHE #AcademicSky

This issue is especially difficult given the lack of correspondence in increases and deceases in ranks between the RRA method and the university guides. Universities aim to improve their ranks in league tables and undertake different strategies to achieve this. Any changes in ranks from one year to the next may be attributed by university staff to strategies that have been put in place to improve the university. However, if the implementation of such strategies has been effective, we would expect to see similar changes in the rankings based on the RRA method and the university guides. The lack of correspondence suggests changes may be more likely to be driven by random fluctuations. By focusing specifically on the university guides, institutions may misattribute changes to these strategies rather than random fluctuation. As such, resources may be allocated to ineffective strategies for improving the institution (e.g., https://blogs.lse.ac.uk/impactofsocialsciences/2021/03/22/the-absurdity-of-universityrankings/.

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Uljana Feest @ufeest.bsky.social · 11/01/2025

I am beyond excited to announce the imminent arrival of my book. Operationism in Psychology. An Epistemology of Exploration: press.uchicago.edu/ucp/books/bo... Brief chapter summaries below (1/10)

press.uchicago.edu

Operationism in Psychology

Analyzes psychological research to offer insights into how methodological and ontological questions are intertwined. Psychology has seen an intense debate about the lack of replicability of results ...

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Susan Swartz @beadmomsw.bsky.social · 11/01/2025

12 years. RIP my darling boy.

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Adam Kucharski @adamjkucharski.bsky.social · 20/12/2024

Also, a reminder that the average effect measured in a population study usually has little predictive value if looking at individual health outcomes: kucharski.substack.com/p/the-popula...

kucharski.substack.com

The popularity of the average

Or why ‘personalised’ health companies sell everyone the same branded product

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Miguel Hernan @miguelhernan.org · 23/12/2024

Upgrade your #causalinference arsenal. A revision of our book "Causal Inference: What If" is available at miguelhernan.org/whatifbook Thanks to everyone who suggested improvements, reported typos, and proposed new citations and material. Enjoy the #WhatIfBook plus code and data. Also, it's free.

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Rich May @richiemay.bsky.social · 17/12/2024

“No causes in, no causes out”(Cartwright, 1994)

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Dax Kellie @daxkellie.bsky.social · 09/12/2024

If you missed my talk but still want to learn how to make your R code more reproducible, my slides are here 🙂: daxkellie.quarto.pub/will-your-co... All the links to packages and resources I mentioned are there, so hopefully this can be a nice reference, too! #ESAus2024 #rstats #quartopub 🧪🌏

Title slide: Will your code run again? Tips for making code reproducible in R

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Aki Vehtari @avehtari.bsky.social · 02/08/2024

All three books I've co-authored are freely available online for non-commercial use: - #Bayesian Data Analysis, 3rd ed (aka BDA3) at stat.columbia.edu/~gelman/book/ - #Regression and Other Stories at avehtari.github.io/ROS-Examples/ - Active Statistics at avehtari.github.io/ActiveStatis...

The cover of Bayesian Data Analysis book

The cover of Regression and Other Stories book

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tal yarkoni @talyarkoni.com · 02/11/2024

there are many reasons why the social sciences remain abyssal pits of methodological despair, but imo the biggest one is that no bridge ever falls down (literally or figuratively) when a social scientist makes an error

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Shravan Vasishth @shravanvasishth.bsky.social · 19/10/2024

Our Introduction to Bayesian Data Analysis for Cognitive Science (with Nicenboim and Schad) is now in production with CRC Press. It will remain freely available here: bruno.nicenboim.me/bayescogsci/

bruno.nicenboim.me

An Introduction to Bayesian Data Analysis for Cognitive Science

An introduction to Bayesian data analysis for Cognitive Science.

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 04/10/2024

1.5 hours of evolutionary game theory in 15 seconds. For something at a slower pace, see the typeset notes: github.com/rmcelreath/V...

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Paul Bürkner @paulbuerkner.com · 01/10/2024

Drafts of the first chapters of my brms Book: Applied Bayesian Regression Modelling Using R and Stan are online: paulbuerkner.com/software/brm... Check it out and let me know what you think!

paulbuerkner.com

Paul Bürkner - The brms Book

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Crystal Lewis @cghlewis.bsky.social · 10/09/2024

When sharing data, it's important that your data meet a set of standard data quality criteria (datamgmtinedresearch.com/clean#clean-...) and is also shared along with documentation (datamgmtinedresearch.com/share#what-d...) to allow for reuse and correct interpretation! osf.io/t8upr

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Sarah May @sarahmay1.bsky.social · 27/09/2024

Well it would require everyone to be honest. I mean, can you imagine a 'research environment' REF report actually describing the research environment rather than just boasting about 'initiatives' and research groups?

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