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Reposted by Felix Thoemmes

Diego Reinero, Ph.D. @diegoreinero.bsky.social · 1d

🚨Excited to announce the full-day Moral Psychology pre-conference at #SPSP2026!

We sold out last year, and with this year’s incredible speaker lineup, we expect the same.

Submit your poster or data blitz abstract by Oct. 23! spsp.wufoo.com/forms/2026-p... There’s a best poster award!

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Alexia Katsanidou @alexiakatsanidou.bsky.social · 1d

Great paper on the state of political science osf.io/preprints/os... by @guygrossman.bsky.social et. al. We have become more diverse, more quantitative, and more collaborative.

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Ruben C. Arslan @ruben.the100.ci · 2d

We're looking for an experimental psychologist in Witten. Contact me if you have questions about the job (I'm not on the commission, so can talk freely :-)
uni-wh.softgarden.io/job/59638545...

Universitätsprofessur für Experimentelle Psychologie (W2-analog) bei Universität Witten/Herdecke

Wir suchen: Universitätsprofessur für Experimentelle Psychologie (W2-analog) (Vollzeit) • Alfred-Herrhausen-Straße 50, 58455 Witten, Deutschland

uni-wh.softgarden.io

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Michael Clemens @mclem.org · 2d

The Paul & Daisy Soros Fellowship "invests in the graduate education of 30 New Americans—immigrants and children of immigrants—poised to significantly contribute to U.S. society, culture, or their academic field. Fellows receive up to $90,000 in financial support over two years."

Why Become a Fellow – Paul & Daisy Soros Fellowships for New Americans

Apply for a Paul & Daisy Soros fellowship and become one of the thirty New Americans— immigrants or the children of immigrants—who are pursuing graduate

pdsoros.org

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Aki Vehtari @avehtari.bsky.social · 2d

I'm looking for a doctoral student with Bayesian background to work on Bayesian workflow and cross-validation (see my publication list users.aalto.fi/~ave/publica... for my recent work) at Aalto University.

Apply through the ELLIS PhD program (dl October 31) ellis.eu/news/ellis-p...

ELLIS PhD Program: Call for Applications 2025

The ELLIS mission is to create a diverse European network that promotes research excellence and advances breakthroughs in AI, as well as a pan-European PhD program to educate the next generation of AI...

ellis.eu

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Julia M. Rohrer @dingdingpeng.the100.ci · 2d

Happy to announce that I'll give a talk on how we can make rigorous causal inference more mainstream 📈

You can sign up for the Zoom link here: tinyurl.com/CIIG-JuliaRo...

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Richard D. Morey @richarddmorey.bsky.social · 4d

Also - contrast b/w the response when I advocate teaching R instead of SPSS -- "No hurry, let's not rush into it" (still waiting) -- & others re: use of LLMs -- "It's inevitable, we're behind; need it implement it ASAP!" -- is telling. Learning to code is freeing. Overhyped LLMs create dependency.

Excerpt from Guest & van Rooij, 2025:

As Danielle Navarro (2015) says about shortcuts through us-
ing inappropriate technology, which chatbots are, we end up dig-
ging ourselves into “a very deep hole.” She goes on to explain:

"The business model here is to suck you in during
your student days, and then leave you dependent on
their tools when you go out into the real world. [...]
And you can avoid it: if you make use of packages
like R that are open source and free, you never get
trapped having to pay exorbitant licensing fees." (pp.
37–38)

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Eiko Fried @eikofried.bsky.social · 4d

Happy fall y'all

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Florian Ederer @florianederer.bsky.social · 5d

Research output after tenure drops off a cliff for business, economics, sociology, and other non-lab fields.

But it remains high post-tenure in lab-based fields such as chemistry, physics, computer science, and engineering.
www.pnas.org/doi/epdf/10....

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Katie Gates @kgates.bsky.social · 5d

UNC is hiring in Quantitative Psychology! Assistant Professor (tenure-track). Please share widely! Find details here: unc.peopleadmin.com/postings/307...

a logo for the carolina tar heels with a ram head

ALT: a logo for the carolina tar heels with a ram head

media.tenor.com

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Max Planck Institute for Psycholinguistics @mpi-nl.bsky.social · 5d

We're seeking the next Director of the Max Planck Institute for Psycholinguistics! Lead cutting-edge research in language & cognition. Nominations (incl. self) due 19 Dec 2025.
mpi.nl/career-education/vacancies/vacancy/nominations-and-self-nominations-sought-position-director-max

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Alexander Wuttke @kunkakom.bsky.social · 5d

Open Science Professor ship at HU Berlin
www.academics.de/jobs/w2-prof...

W2-Professur "Open Science" an der Philosophischen Fakultät - Humboldt-Universität zu Berlin

Humboldt-Universität zu Berlin bietet Stelle als W2-Professur "Open Science" an der Philosophischen Fakultät in Berlin - jetzt bewerben!

www.academics.de

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Mattan S. Ben-Shachar 🎗️🇮🇱🇺🇦 @mattansb.msbstats.info · 5d

Starting up a new @quarto.org file.

Filling in the yaml header.

title: "supporting the null in the Bayesian framework"
author: -- copilot suggests @mjskay.com

What a flex! 💪

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Paul Hünermund @p-hunermund.com · 5d

Post a favorite econ paper: Lichter et al. (2021, JEEA) @sigginho.bsky.social

Regions with higher Stasi spy density in East Germany still show lower trust, lower incomes, higher unemployment, and less entrepreneurship decades after reunification.

Open-access link: doi.org/10.1093/jeea...

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Josh Miller @jdmiller.bsky.social · 5d

Apropos of recent open science conversations - this paper is an awesome primer for grad students and faculty who want to learn more: online.ucpress.edu/collabra/art...

Easing Into Open Science: A Guide for Graduate Students and Their Advisors

This article provides a roadmap to assist graduate students and their advisors to engage in open science practices. We suggest eight open science practices that novice graduate students could begin ad...

online.ucpress.edu

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GESIS Training @gesistraining.bsky.social · 6d

Want to bring causal thinking into qualitative or mixed methods research? @macartan.bsky.social & @alanjacobs.bsky.social show how to build causal models & use Bayesian reasoning to link theory with data, guide case & method choices, & combine within- & cross-case evidence.
👉 t1p.de/qual_mix_meth_26

GESIS Workshop
Causal Models for Qualitative and Mixed Methods Research
27 to 28 January 2026 / Cologne
Macartan Humphreys & Alan M. Jacobs

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Jennifer Tackett @jnfrltackett.bsky.social · 6d

We have a new preprint out - continuing to try and move the needle on improving research in clinical psych

Josh Miller @jdmiller.bsky.social · 6d

New paper led by @drlynam.bsky.social on the need for more training in and engagement with open science practices in clinical psych programs. It has been difficult to make progress due to a variety of barriers, including students working in labs uninterested or hostile to these approaches.

PsyArXivBot @psyarxivbot.bsky.social · 7d

The Open Science Movement and Clinical Psychology Training: Rigorous Science is Transparent Science: https://osf.io/s46wd

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Pam Davis-Kean, PhD @umpamdk.bsky.social · 6d

@psychscience.bsky.social Submission site for Barcelona 2026 opens Oct. 30th!!! Join us in Spain for the first APS to be held outside the U.S. Many new ways to interact and to share psychological research being done around the world. www.psychologicalscience.org/conventions/...

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Julia M. Rohrer @dingdingpeng.the100.ci · 6d

Just finished reading this *excellent* article by Gabriel et al. which discusses which effects can be identified in randomized controlled trials. With DAGs!>

link.springer.com/article/10.1...

Elucidating some common biases in randomized controlled trials
using directed acyclic graphs

Although the ideal randomized clinical trial is the gold standard for causal inference, real randomized trials often suffer
from imperfections that may hamper causal effect estimation. Stating the estimand of interest can help reduce confusion
about what is being estimated, but it is often difficult to determine what is and is not identifiable given a trial’s specific
imperfections. We demonstrate how directed acyclic graphs can be used to elucidate the consequences of common imperfections,
such as noncompliance, unblinding, and drop-out, for the identification of the intention-to-treat effect, the total
treatment effect and the physiological treatment effect. We assert that the physiological treatment effect is not identifiable
outside a trial with perfect compliance and no dropout, where blinding is perfectly maintained

Table 1 showing the Identifiability of target estimands depending on whether there is blinding, full compliance, and no drop-out

An example DAG from the paper.
Fig. 4: A blinded trial with noncompliance.

U are unobserved confounders, Z is treatment assignment, C is compliance, X is the realized treatment, S is the subject's physical and mental health status, Xself and Xcln are the treatment that the participant and the clinician believed the participant received, Y is the outcome.

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Peter Tennant @pwgtennant.bsky.social · 7d

Very excited to be in Luxembourg - with the Aging, Cancer, & Disparaties Research Unit green mascot - to launch the RESCOM lecture series in causal inference!

Future speakers from an amazing lineup include @georgiatomova.bsky.social, @miguelhernan.org, Mats Stenrund, & @dingdingpeng.the100.ci!

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Kevin M. King @kevinmking.bsky.social · 6d

Despite heroic efforts by a small cadre of people in the field, the vast majority of senior PIs in clinical psychology continue to be uninterested or hostile to OS practices.

It makes me think they just don't care, and it's really depressing.

Josh Miller @jdmiller.bsky.social · 6d

New paper led by @drlynam.bsky.social on the need for more training in and engagement with open science practices in clinical psych programs. It has been difficult to make progress due to a variety of barriers, including students working in labs uninterested or hostile to these approaches.

PsyArXivBot @psyarxivbot.bsky.social · 7d

The Open Science Movement and Clinical Psychology Training: Rigorous Science is Transparent Science: https://osf.io/s46wd

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Rich Lucas @richlucas.bsky.social · 6d

We already know that lagged effects in CLPMs are likely to be upwardly biased, but just how easy is it to find significant effects? Way too easy. I tested CLPMS in 100 randomly selected pairs of correlated variables and found significant effects in 98 of them. New preprint: osf.io/preprints/ps...

OSF

osf.io

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rogier kievit @rogierk.bsky.social · 7d

Gather round, all those bayes curious, pragmatic, committed or indifferent, for an elegant and flexible way to approach reliability estimation using bayesian measurement models! All thoughts and ideas welcome

Giacomo Bignardi @bignardi.bsky.social · 7d

New preprint with @rogierk.bsky.social @paulbuerkner.com - we introduce "relative measurement uncertainty" - a reliability estimation method that's applicable across a broad class of Bayesian measurement models (e.g., generative-, computational- and item response theory-models osf.io/h54k8

OSF

osf.io

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David Pizarro @peez.bsky.social · 7d

We're hiring!

Felix Thoemmes @felixthoemmes.bsky.social · 7d

Come work with me at Cornell University. We are hiring an open-rank tenure-track professor in social / developmental with a focus on relationship science and human bonding.

academicjobsonline.org/ajo/jobs/30665

Cornell University, Psychology

Job #AJO30665, WDR-00055302 Open Rank, Tenure-Track Faculty Position, Psychology, Psychology, Cornell University, Ithaca, New York, US

nam12.safelinks.protection.outlook.com

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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 8d

Was asked about collinearity again, so here's Vahove's 2019 post on why it isn't a problem that needs a solution. Design the model(s) to answer a formal question and free your mind janhove.github.io/posts/2019-0...

tl;dr

Collinearity is a form of lack of information that is appropriately reflected in the output of your statistical model.
When collinearity is associated with interpretational difficulties, these difficulties aren’t caused by the collinearity itself. Rather, they reveal that the model was poorly specified (in that it answers a question different to the one of interest), that the analyst overly focuses on significance rather than estimates and the uncertainty about them or that the analyst took a mental shortcut in interpreting the model that could’ve also led them astray in the absence of collinearity.
If you do decide to “deal with” collinearity, make sure you can still answer the question of interest.

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