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Amelia Zein

@ameliazein.bsky.social
1.2K followers 3.4K following 18 posts

A research associate (@ CAIS) and an assistant professor (@ Universitas Airlangga, Indonesia). PhD @ LMU Munich. Science, religion, and everything else in between. Passionate about metascience.

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Reposted by Amelia Zein
ejwagenmakers.bsky.social @ejwagenmakers.bsky.social · 02/07/2026
Now available as free download: JASP 0.98 with optional AI support! Blog post: jasp-stats.org/2026/07/02/i...
jasp-stats.org
Introducing JASP 0.98: Fully Integrated AI Support - JASP - Free and User-Friendly Statistical Software
We are proud to announce that JASP 0.98 has been released and is now available on our download page. The major innovation in JASP 0.98 is the (optional!) inclusion of fully integrated AI support. This...
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Erez Yoeli @erezyoeli.bsky.social · 02/07/2026
Trust in science is falling, but: - it remains high - the drop is no larger than for other institutions - the reduction is concentrated amongst the political right www.nature.com/articles/d41...
nature.com
Have people stopped trusting science? The data tell a surprising story
Some say there’s a global crisis of trust — but research reveals where the real problems lie.
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Mark Rubin @markrubin.bsky.social · 01/07/2026
Great symposium this morning at the #EASP2026 conference: “Who critiques the critique? Toward a reflexive metascience,” with presenters @ameliazein.bsky.social, @mariogollwitzer.bsky.social, @fgabarrot.bsky.social, and me!
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Dan Quintana @dsquintana.bsky.social · 14/11/2025
Our paper on improving statistical reporting in psychology is now online 🎉 As a part of this paper, we also created the Transparent Statistical Reporting in Psychology checklist, which researchers can use to improve their statistical reporting practices www.nature.com/articles/s44...
Transparent and comprehensive statistical reporting is critical for ensuring the credibility, reproducibility, and interpretability of psychological research. This paper offers a structured set of guidelines for reporting statistical analyses in quantitative psychology, emphasizing clarity at both the planning and results stages. Drawing on established recommendations and emerging best practices, we outline key decisions related to hypothesis formulation, sample size justification, preregistration, outlier and missing data handling, statistical model specification, and the interpretation of inferential outcomes. We address considerations across frequentist and Bayesian frameworks and fixed as well as sequential research designs, including guidance on effect size reporting, equivalence testing, and the appropriate treatment of null results. To facilitate implementation of these recommendations, we provide the Transparent Statistical Reporting in Psychology (TSRP) Checklist that researchers can use to systematically evaluate and improve their statistical reporting practices (https://osf.io/t2zpq/). In addition, we provide a curated list of freely available tools, packages, and functions that researchers can use to implement transparent reporting practices in their own analyses to bridge the gap between theory and practice. To illustrate the practical application of these principles, we provide a side-by-side comparison of insufficient versus best-practice reporting using a hypothetical cognitive psychology study. By adopting transparent reporting standards, researchers can improve the robustness of individual studies and facilitate cumulative scientific progress through more reliable meta-analyses and research syntheses.
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Erika Hall @erikahall.bsky.social · 06/11/2025
My favorite comment on the FT story
Personally I'd be impressed if they could make something as smart as an ant. Ants only have 250,000 neurons, which is pretty small compared with GPT-5's reputed more than one trillion parameters. And yet ants are able to survive all by themselves in this complex world of ours, without endless infusions of investor capital or government subsidies. I don't think GPT-5 could do that.
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Miriam Posner @miriamposner.com · 28/10/2025
Whatever strategy you’re about to suggest, we’ve thought about it. docs.google.com/document/d/1...
docs.google.com
ChatGPT Harm Reduction for Writing Assignments
ChatGPT Harm Reduction for Writing Assignments Because this document has escaped containment, a couple points of explanation. I wrote this for myself and a few colleagues as we work out how to handle...
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Andrei Cimpian @andreicimpian.bsky.social · 22/09/2025
💖This paper has been ~11 years in the making - and probably my favorite project of all time. Thrilled to see it in @pnas.org! I'm so lucky that Zach decided to do a second PhD and join my lab @psychillinois.bsky.social back in 2014 - a fabulous scientist & human being! www.pnas.org/doi/10.1073/...
Historical and experimental evidence that inherent properties are overweighted in early scientific explanation
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Marlene Altenmüller @marlephie.bsky.social · 22/09/2025
✨ LUCKY COINCIDENCES ✨ Have you ever come across a surprising, accidental discovery that felt meaningful and motivated you to further engage with it? In our new paper now out in JASP (doi.org/10.1111/jasp...), we explore such serendipitous experiences in museums and beyond. 1/5 🧵
doi.org
Lucky Coincidences: Experiencing Serendipity in Museums and Beyond
Serendipity is the unintentional, accidental discovery of something new or surprising that feels positive and meaningful for the individual. Four studies (N1 = 1638; N2 = 279; N3 = 520; N4 = 452) exa...
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Kelly Bodwin @kellybodwin.com · 18/09/2025
Shannon's slides are always so unbelievably clear and helpful!!! github.com/shannonpileg... I'm having "Ohhhhh that's what that means" moments every 10 seconds here. #positconf2025
github.com
GitHub - shannonpileggi/practical-renv: A posit::conf(2025) talk.
A posit::conf(2025) talk. Contribute to shannonpileggi/practical-renv development by creating an account on GitHub.
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Malte Elson @malte.the100.ci · 17/09/2025
I'm afraid we've been at it again
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Anne Urai @anne-urai.bsky.social · 10/02/2025
Feeling like academia is in pretty bad shape? You're not alone. @clarekelly.bsky.social and I previously wrote about the need to collectively rethink and reshape scientific practice: the academic doughnut. Read more at elifesciences.org/articles/84991 But, have these ideas changed anything? 👇
Doughnut academia.
Adapting the “doughnut” model of economics to the academic world enables us to visualize the inner social foundations that universities should provide, and the outer human and planetary boundaries that universities need to avoid overshooting. Note that the ordering of elements within the inner and outer rings is random; there is no direct pairing between foundations and ceilings.

Adapted from Raworth, 2017 under a CC-BY-SA license.Seven ways to think like a 21st century scientist.
1. Change the goal: from a business that produces papers and graduated students, towards a university that works towards the inside space of the academic doughnut. 2. Get savvy with systems: from feeling like a cog in the university machine, towards being gardeners of our academic system. 3. See the big picture: from academics who look out over the world from their ivory tower, towards scholarship which accepts its own embeddedness in (and dependence on) society and the planet. 4. Create to regenerate: from a rat race where we tread water, towards “slow scholarship” that values community building, deep thinking and rest crucial for intellectual work. 5. Nurture human nature: from the lone genius, towards team science. 6. Design to distribute: from a funding system where the rich get richer, towards a fair distribution of opportunities and resources. 7. Be agnostic about growth: from a focus on increasing numbers of papers, citations and students, towards rebuilding trust in our own academic communities and with society.
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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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Alisa Bokulich @alisabokulich.bsky.social · 10/09/2025
Happy birthday to the #19thC geoscientist & pragmatist philosopher Charles Sanders Peirce "Science . . . [is] a living historic entity. . . .As such, it does not consist so much in knowing, nor even in 'organized knowledge,' as it does in diligent inquiry into truth" CP 1.44 #philsci #philsky ⚒️
Copy of plaque at Peirce's birthplace in Cambridge MA with words "CHARLES SANDERS PEIRCE
SCIENTIST. MATHEMATICIAN LOGICIAN, PHILOSOPHER WAS BORN
IN THIS HOUSE ON SEPTEMBER 10,1839
ONE OF AMERICA'S MOST ORIGINAL AND VERSATILE INTELLECTS"A photo of a middle aged Charles Peirce standing legs crossed with hand on hip in a 19thC suit.
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John Paul Helveston @jhelvy.bsky.social · 29/08/2025
Excited to announce that our paper with @pingfanhu.bsky.social and Bogdan Bunea on our #rstats package {surveydown} is now published in @plosone.org The paper compares the benefits of using a code-based approach to survey design, leveraging #quarto and #shiny journals.plos.org/plosone/arti...
journals.plos.org
surveydown: An open-source, markdown-based platform for programmable and reproducible surveys
This paper introduces the surveydown survey platform. With surveydown, researchers can create surveys that are programmable and reproducible using markdown and R code, leveraging the Quarto publicatio...
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Ian Hussey @ianhussey.mmmdata.io · 18/08/2025
{truffle} is an R package for teaching users to process data. Semi-realistic psychological datasets with predetermined effects (via `truffles_` functions) are then hidden in common data processing headaches (via `dirt_` functions) for students to clean and analyze. mmmdata.io/posts/2025/0...
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Amelia Zein @ameliazein.bsky.social · 11/08/2025
In a newly published registered report by @mariogollwitzer.bsky.social, Moritz Heene, and me, we found that people perceive the relationship between science and religion differently, as described by Ian G. Barbour in his typology. We made a tool to scrutinize Barbour's typology...
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Amelia Zein @ameliazein.bsky.social · 09/08/2025
I remember the early days of my bachelor, Gergen's "Social Psychology as History" was the first scientific article I read. Was shoved down my throat in a socpsych intro class. I barely understood English back then, let alone psych theory. 18 yrs later, I find it super useful for my upcoming project.
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Richard D. Morey @richarddmorey.bsky.social · 08/08/2025
Paper drop, for anyone interested in #metascience, #statistics, or #metaanalysis! @clintin.bsky.social and I show in a new paper in JASA that the P-curve, a popular forensic meta-analysis method, has deeply undesirable statistical properties. www.tandfonline.com/doi/full/10.... 1/?
Cover page for the manuscript: Morey, R. D., & Davis-Stober, C. P. (2025). On the poor statistical properties of the P-curve meta-analytic procedure. Journal of the American Statistical Association, 1–19. https://doi.org/10.1080/01621459.2025.2544397Abstract for the paper: The P-curve (Simonsohn, Nelson, & Simmons, 2014; Simonsohn, Simmons, & Nelson, 2015) is a widely-used suite of meta-analytic tests advertised for detecting problems in sets of studies. They are based on nonparametric combinations of p values (e.g., Marden, 1985) across significant (p < .05) studies and are variously claimed to detect “evidential value”, “lack of evidential value”, and “left skew” in p values. We show that these tests do not have the properties ascribed to them. Moreover, they fail basic desiderata for tests, including admissibility and monotonicity. In light of these serious problems, we recommend against the use of the P-curve tests.
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Michael Inzlicht @minzlicht.bsky.social · 23/07/2025
For decades, psychologists believed reminding people of death would make them fry themselves in tanning booths, recommend harsher punishments for prostitutes, support martyrdom, and spend more on luxury goods. Rigorous testing revealed: nope. But dead theories have a way of refusing to stay buried.
open.substack.com
Psychologists Have Been Wrong About Death For 40 Years
Smart people are sometimes the last to realize that the cognitive ship they are captaining is about to sink.
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Marlene Altenmüller @marlephie.bsky.social · 18/07/2025
🚨 Fresh off the press 🚨 Our #TISP spin-off paper on the relationship between #ConspiracyBeliefs and individual #victimhood is now out! doi.org/10.1002/ejsp... 1/8 🧵
doi.org
Victims of Conspiracies? An Examination of the Relationship Between Conspiracy Beliefs and Dispositional Individual Victimhood
Conspiracy beliefs have been linked to perceptions of collective victimhood. We adopt an individual perspective on victimhood by investigating the relationship between conspiracy beliefs and the indi....
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Amelia Zein @ameliazein.bsky.social · 15/07/2025
Today, I received a thank-you email from someone in Australia. They said our tutorial paper was exceptionally helpful and asked if I was available for a brief chat. Academia can be sometimes… brutal, but something like this is enough to keep me going🤗
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Tamás Nagy @nagyt.bsky.social · 11/07/2025
🚨 New study alert! We're excited to share our "Bestiary of Questionable Research Practices in Psychology" in #AMPPS. We tackle the credibility crisis in research by defining, collecting, and categorizing QRPs using a community consensus method. 🧵#OpenScience #QRPs @psychscience.bsky.social
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Amelia Zein @ameliazein.bsky.social · 11/07/2025
Over the past few weeks, I was invited to talk about a bit of my research interest at Universitas Airlangga and Universitas Indonesia. I discussed what past evidence says about how people use scientific and religious explanations. Slides are accessible here rameliaz.github.io/talk/2025-ivs/
rameliaz.github.io
Can Science and Religion Coexist? | Rizqy Amelia Zein
A modern, beautiful, and easily configurable blog theme for Hugo.
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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 09/07/2025
How can we reform science? I have some ideas. But I am not sure you’ll like them, because they don’t promise much. elevanth.org/blog/2025/07...
elevanth.org
Which Kind of Science Reform
What hope is there for science reform, if we can't agree on what to reform? Right now, principles are more important than practices.
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moin syed @syeducation.bsky.social · 05/07/2025
New post! "A Tale of Two Science Reform Movements," in which I compare the recent #Metascience2025 and #SIPS2025 conferences, and find that I am much more at home at one than the other. getsyeducated.substack.com/p/a-tale-of-...
getsyeducated.substack.com
A Tale of Two Science Reform Movements
Reflections from meetings of Metascience 2025 and the Society for the Improvement of Psychological Science
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Brian Nosek @briannosek.bsky.social · 28/06/2025
"Science is trustworthy because it doesn’t trust itself" cen.acs.org/research-int...
cen.acs.org
Amid White House claims of a research ‘replication crisis,’ scientists offer solutions
Efforts have been underway for years to improve the replicability of research studies, but some are skeptical of the US government’s motivations to help
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Amelia Zein @ameliazein.bsky.social · 25/06/2025
We are deeply honored to have Marlene (@marlephie.bsky.social) here in Surabaya! The Airlangga folks truly enjoyed our conversation with Marlene! We will fondly remember the knowledge, experience, and cross-cultural exchange involved in this visit😊
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Michèle Nuijten @michelenuijten.bsky.social · 19/06/2025
📣New Preprint Alert! Esther Maassen meticulously simulated the effect of p-hacking and publication bias on effect size & heterogeneity estimates. 💡bad: selective outcome reporting & optional dropping 💡bad: publication bias 💡not so bad: optional stopping/outlier removal osf.io/preprints/ps...
osf.io
OSF
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Institute for Replication @i4replication.bsky.social · 29/05/2025
GiveWell sought an independent check on the evidence supporting >$1 billion it has granted to its top charities. This fall, Alex Cohen asked whether we could obtain the datasets needed to reproduce the underlying RCTs. We said yes; charging only a modest fee to cover our time. 🧵 + 🐀 + blog post!
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Mario Gollwitzer @mariogollwitzer.bsky.social · 05/05/2025
🎺COME WORK WITH US @LMU Munich on a new research project: job-portal.lmu.de/jobposting/d.... (postdoc/3 years/full-time). We will develop and evaluate an agile and needs-oriented Research Data Management certificate course for researchers in psychology. Application Deadline: *May 31*
job-portal.lmu.de
Wissenschaftlicher Mitarbeiter / Wissenschaftliche Mitarbeiterin (m/w/d)
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kottke.org @kottke.org · 28/04/2025
Studio Ghibli has uploaded hundreds of beautiful still images from almost all of their films, including all of the major ones. These individual artworks are free to download “by individual fans to further enjoy Studio Ghibli films”. [kottke.org]
kottke.org
Hundreds of Free Images From Studio Ghibli Films
Well this is just wonderful: Studio Ghibli has uploaded hundreds of high-resolution still images from almost all of their films, including all of the major ones: Princess Mononoke, Sprited Away, M
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Léo Fitouchi @lfitouchi.bsky.social · 11/02/2025
Where do moralizing religions come from? Useless cognitive by-products?Cultural group selection for complex societies? Our Psych Review paper argues: neither. Let’s rethink their cognitive & evolutionary origins🧵 w/ @manvir.bsky.social @nbaumard @jbaptistandre.bsky.social doi.org/10.1037/rev0...
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Andreas Kirsch @blackhc.bsky.social · 07/01/2025
Ever wondered why presenting more facts can sometimes *worsen* disagreements, even among rational people? 🤔 It turns out, Bayesian reasoning has some surprising answers - no cognitive biases needed! Let's explore this fascinating paradox quickly ☺️
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Prashant Garg @prashantgarg.bsky.social · 06/12/2024
Public trust in science is more important than ever. But what happens when scientists openly share their political opinions on social media? Our updated paper with @eleala.bsky.social & @walraslaw.bsky.social shows how academics’ political expression affects their credibility
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Kelsey Starr @madeofstarrstuff.bsky.social · 14/11/2024
Republicans and Democrats in the U.S. differ in what terms they feel describe research scientists. Read more in our new report about US trust in scientists! pewrsr.ch/3USzH0S
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Amelia Zein @ameliazein.bsky.social · 14/11/2024
Super excited to share a new tutorial paper I've co-authored with one of 🇮🇩's brightest minds, Hanif Akhtar. If you're interested in IRT and deal with polytomous data daily, but have no idea where to start, maybe this is for you? doi.org/10.1002/ijop...
doi.org
Getting started with the graded response model: An introduction and tutorial in R
This tutorial introduces the graded response model (GRM), a tool for testing measurement precision within the item response theory (IRT) paradigm, which is useful for informing researchers about the ....
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Willem-Jelle @willem-jelle.bsky.social · 13/11/2024
What if you combine a comic with real data? 2024 is on track to be the first year with a temperature above 1.5 °C. The visualisation speaks for itself 🔥🔥🔥 Analysis and graph in #RStats and finished the design in #Figma. More on GitHub.com/Willem-Jelle. Original comic by Semi-Rad ❤️
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Jeremy Allen @jeremy-data.bsky.social · 09/11/2024
Wow. It has been just 3 weeks since I made the #RStats Starter Pack. At the time, Elon had announced blocking rules on X were being changed. I was surprised there wasn't an rstats starter pack here yet, so voila! I added more to it this week, so check it again and follow more. go.bsky.app/Ki7PjpS
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David Ho @davidho.bsky.social · 10/11/2024
A gentle reminder that if we miss the 1.5°C target (and we certainly will), the next target is 1.51°C and not 2°C. We need to keep fighting. Every tonne of CO₂ emitted makes the job of future CO₂ removal harder, and every 0.01°C of temperature increase makes the world more chaotic and dangerous.
Cover from The Economist from two years ago "Say goodbye to 1.5°C; why climate policy is off target". It has a graphic of the Earth with an apple on its head, and a arrow shot through the Earth.
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Postcard From The Past @pastpostcard.bsky.social · 06/11/2024
Trying to ignore the doom and gloom of the world.
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Katharine Hayhoe @katharinehayhoe.com · 17/10/2024
As a climate scientist, here’s 3 things I wish everyone knew: 1. How much of our current warming is human-caused? All of it + then some. 2. What happens from year to year? That’s weather. For climate, see decadal trends. 3. What’s the most important thing you can do? Not recycling; this ⬇️
A screenshot of a social media post giving a list of the most effective things in individual can do to make a difference on climate change, according to social science, beginning with talking about it!
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Neil Lewis, Jr. @neillewisjr.bsky.social · 29/09/2024
Oxford University launched a Palestine Crisis Scholarship which "provides access to higher education to students displaced by the humanitarian crisis in Gaza and the West Bank through the provision of full graduate scholarships to study at Oxford." More info here: www.ox.ac.uk/admissions/g...
ox.ac.uk
Palestine Crisis Scholarship Scheme | University of Oxford
AboutThis scheme provides access to higher education to students displaced by the humanitarian crisis in Gaza and the West Bank through the provision of full graduate scholarships to study at Oxford.
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moin syed @syeducation.bsky.social · 30/09/2024
Interested in how Islamophobia has been conceptualized and measured? Want to read 93 pages on the topic? Then check out our new review paper led by the incomparably thorough Ummul Kathawalla: doi.org/10.1111/asap...
doi.org
SPSSI Journals
The term Islamophobia is used in research studies; however, it is evident many researchers do not similarly use the term and, subsequently, measure the construct. We evaluate measures based upon thei...
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Joe Bak-Coleman @jbakcoleman.bsky.social · 27/09/2024
I've long wanted to write a blog post about how you can create a really solid stack that achieves most Open Science goals in a way that exceeds what you'd get from depositing somewhere like OSF. The recent *events* have driven home how much room there is for improvement in how we store things.
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Bret Beheim @babeheim.bsky.social · 16/09/2024
Testing out the fancy new video support with my log Galton board.
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Tatyana Deryugina @tderyugina.bsky.social · 18/07/2024
How should you deal with journal rejections? Some suggestions below.
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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 bookThe cover of Regression and Other Stories bookThe cover of Active Statistics book
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Amelia Zein @ameliazein.bsky.social · 10/06/2024
✨What happens psychologically when ppl relate science & religion?✨ Ppl perceive it as a conflict, unless they are „motivated“ to reconcile and willing to be „cognitively flexible“. A new paper is out w/ @marlephie.bsky.social & @mariogollwitzer.bsky.social🎉 🔴: psycnet.apa.org/doiLanding?d...
psycnet.apa.org
APA PsycNet
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Brendan Nyhan @brendannyhan.bsky.social · 28/04/2024
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Charles O’Connor @coconnor8.bsky.social · 24/04/2024
@carlbergstrom.com If you see Runi the Great, pls call the number
Flyer in a store window. “Missing Crow. name: Runi the Great (does not respond to name). Description: all black, able to fly, looks and acts EXACTLY like a crow, very intelligent. Last seen Halloween night 2023. Please call Kreneth. 802 3972891
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