Arthur Chatton
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achatton.bsky.social
Arthur Chatton
@achatton.bsky.social
200 followers 150 following 4 posts
Assistant professor in Biostatistics. School of Public Health, University of Montreal. Causal inference - Casual chess. 🇫🇷🇪🇺 living in lovely 🇨🇦
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Reposted by Arthur Chatton
dsquintana.bsky.social
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.
November 14, 2025 at 8:43 PM
Reposted by Arthur Chatton
dsquintana.bsky.social
“Google's strategic transformation into an AI-first company fundamentally conflicts with maintaining niche academic services like Scholar”
November 11, 2025 at 10:30 PM
Reposted by Arthur Chatton
drlutzboehm.bsky.social
You are a Post-Padawan now!
November 5, 2025 at 3:24 PM
Reposted by Arthur Chatton
scientificdiscovery.dev
In general I think it's hard to combat scientific misinformation when some of the best research is locked behind an academic paywall, while lots of nonsense gets published free for everyone to read in predatory journals.
September 28, 2025 at 5:25 PM
Reposted by Arthur Chatton
pwgtennant.bsky.social
The TARGET reporting guidelines for target trial emulation studies have arrived!

#EpiSky #CausalSky

jamanetwork.com/journals/jam...
TARGET 2025 Statement
This Special Communication introduces the Transparent Reporting of Observational Studies Emulating a Target Trial (TARGET) 2025 guideline, a consensus-based guidance for reporting observational studie...
jamanetwork.com
September 3, 2025 at 4:20 PM
Reposted by Arthur Chatton
dingdingpeng.the100.ci
Folks, always share your code. It doesn’t have to be perfect to be helpful. And if you feel that it’s still too messy or not sufficiently clean to be shared, you shouldn’t submit yet. After all, there could be mistakes in your mess.
May 9, 2025 at 10:21 AM
Reposted by Arthur Chatton
epijobs.bsky.social
Assistant or Associate Professor in Epidemiology
Montreal, Quebec, Canada United States #Epijobs
careers.apha.org/jobs/2125722...
May 5, 2025 at 2:09 AM
Reposted by Arthur Chatton
dingdingpeng.the100.ci
Just discovered this excellent paper on mediation analysis in Psych Methods. The focus defining various effects; I really appreciate how the authors contrast the "traditional" approach with "causal" mediation analysis. Great job picking up readers where they are!
www.researchgate.net/publication/...
Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn Trang Quynh Nguyen, Ian Schmid, Elizabeth A. Stuart Johns Hopkins Bloomberg School of Public Health The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements – effect definitions with causal interpretation, clarification of assumptions required for e ect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, which may be confusing to researchers unfamiliar with causal inference or unfamiliar with mediation. The goal of this paper is to help ease the understanding and adoption of causal mediation analysis. It starts by highlighting a key difference between the causal inference and traditional approaches to mediation analysis and making a case for the need for explicit causal thinking and the causal inference approach in mediation analysis. It then explains in as-plain-as-possible language existing effect types, paying special attention to motivating these e ects with different types of research questions, and using concrete examples for illustration. This presentation differentiates two perspectives (or purposes of analysis): the explanatory perspective (aiming to explain the total e ect) and the interventional perspective (asking questions about hypothetical interventions on the exposure and mediator, or hypothetically modified exposures). For the latter perspective, the paper proposes tapping into a general class of interventional effects that contains as special cases most of the usual effect types – interventional direct and indirect effects, controlled direct effects and also a generalized interventional direct effect type, as well as the total effect and overall effect...
April 16, 2025 at 9:12 AM
Reposted by Arthur Chatton
rush-099.bsky.social
Hot off the press! 📣📣In this tutorial we illustrate available multiple imputation approaches for handling longitudinal data including when they are clustered within higher level clusters. A reproducible example with R and Stata code provided! #OpenAccess

onlinelibrary.wiley.com/doi/10.1002/...
Multiple Imputation for Longitudinal Data: A Tutorial
Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thu....
onlinelibrary.wiley.com
January 27, 2025 at 4:14 AM
Reposted by Arthur Chatton
i4replication.bsky.social
New research alert! Our study investigates the effectiveness of human-only, AI-assisted, and AI-led teams in assessing the reproducibility of quantitative social science research. We've got some surprising findings!
January 22, 2025 at 2:23 AM
Reposted by Arthur Chatton
donskerclass.bsky.social
A strong contender, at least: arxiv.org/abs/2405.08675
December 27, 2024 at 5:13 PM
Reposted by Arthur Chatton
clemley.bsky.social
📣 Do you want to learn about recent advances in causal inference?

Colleagues at INSERM are organising a workshop gathering international experts in the field. Bonus: it's happening in two amazing locations 🌇🇫🇷
December 18, 2024 at 9:02 AM
Reposted by Arthur Chatton
maartenvsmeden.bsky.social
NEW PREPRINT

A detailed overview of 32 popular predictive performance metrics for prediction models

arxiv.org/abs/2412.10288
December 16, 2024 at 8:44 AM
Reposted by Arthur Chatton
pausalz.bsky.social
best I got for Schrodinger's regression
Schrodinger's cat, but the radioactive source is labeled "reviewers' comments", the hammer for the poison is labeled "editor's decision", and the alive cat is labeled "beta-hat is machine learning" and the dead cat is labeled "beta-hat is not machine learning"
November 27, 2024 at 5:32 PM
Reposted by Arthur Chatton
dszlosek.bsky.social
The "Leaky prognostic model adoption pipeline" by @maartenvsmeden.bsky.social and colleagues is probably one of my most used figures when discussing building useful clinical prediction models. See the full paper here: publications.ersnet.org/content/erj/... #MLSky #stats #rstats #statistics
Leaky Clinical Prediction Models
November 14, 2024 at 3:29 PM
Reposted by Arthur Chatton
maartenvsmeden.bsky.social
Was recently reminded of David Hand's alternative missing data taxonomy renaming the (in)famous taxonomy MCAR/MAR/MNAR by Donald Rubin to NDD/SDD/UDD. I am not generally a fan of renaming things, but this might be the exception

Source: rss.org.uk/training-eve...
November 11, 2024 at 9:13 AM
Reposted by Arthur Chatton
statsepi.bsky.social
You can't understand what tx effects can be estimated using clinical RCTs without understanding the REAL-WORLD context that clinical RCTs are conducted in. How patients are enrolled, and how medicines are "approved" are critical parts of this context.

(ICYMI)

statsepi.substack.com/p/a-conversa...
A conversation on treatment effects
The trial statistician and the clinical investigator took a step back to admire their creation.
statsepi.substack.com
November 8, 2024 at 2:26 PM
Reposted by Arthur Chatton
epidbydesign.bsky.social
Since I have new followers, time to re-up this:

do you want to use my textbook (EPIDEMIOLOGY BY DESIGN) to teach? I have materials to share! I will give you lecture notes and exercises and exams and more!!
epidbydesign.bsky.social Daniel Westreich @epidbydesign.bsky.social · Jul 28
If you teach epidemiology and might be interested in using my textbook (EPIDEMIOLOGY BY DESIGN) --

I will send you ALL MY TEACHING MATERIALS (lecture slides; practice problems; exercises; exams + keys; sample syllabi...).

Just ask! And also www.epidemiologybydesign.com
Epidemiology By Design
www.epidemiologybydesign.com
September 12, 2024 at 4:22 PM
Reposted by Arthur Chatton
statsepi.bsky.social
There are so many people out there trying to "fix" how we teach statistics and statistical thinking. Here is just one of many many examples. Empower them! Sure, it costs money to revamp curricula, but we do it all the time in medicine. Why not for stats!?

www.tandfonline.com/doi/full/10....
Open Case Studies: Statistics and Data Science Education through Real-World Applications
With unprecedented and growing interest in data science education, there are limited educator materials that provide meaningful opportunities for learners to practice statistical thinking, as defin...
www.tandfonline.com
October 28, 2024 at 11:40 AM
Reposted by Arthur Chatton
pausalz.bsky.social
If you're looking for a spoOoOoOoky epidemiology paper for Halloween, might I recommend this one

TLDR: the Kaplan-Meier estimator (with late entries) is haunted

www.ncbi.nlm.nih.gov/pmc/articles...
Hidden Imputations and the Kaplan-Meier Estimator
The Kaplan-Meier (KM) estimator of the survival function imputes event times for right-censored and left-truncated observations, but these imputations are hidden and therefore sometimes unrecognized b...
www.ncbi.nlm.nih.gov
October 15, 2024 at 4:22 PM
Reposted by Arthur Chatton
statsepi.bsky.social
Every so often I'm reminded that a few of my tweets were included in a scientific paper and I'm still not exactly sure how I feel about that.

trialsjournal.biomedcentral.com/articles/10....
October 9, 2024 at 11:40 AM
Reposted by Arthur Chatton
mcbazacophd.bsky.social
Words cannot describe how wonderful libraries are. They are true treasure of society. The fact that they are getting their funding cut so police forces can have tanks and tactical gear is a true crime against culture.

Libraries are one of the greatest things in earth, no hyperbole.
Ellie sitting at a table coloring at the library, with bookshelves as far as the eye can see.
June 16, 2024 at 2:36 PM
Reposted by Arthur Chatton
engra.me
"A random half of panelists were shown a CV and only a one-paragraph summary of the proposed research, while the other half were shown a CV and a full proposal. We find that withholding proposal texts from panelists did not detectibly impact their proposal rankings"
link.springer.com/article/10.1...
Do grant proposal texts matter for funding decisions? A field experiment - Scientometrics
Scientists and funding agencies invest considerable resources in writing and evaluating grant proposals. But do grant proposal texts noticeably change panel decisions in single blind review? We report...
link.springer.com
June 3, 2024 at 9:26 PM
Reposted by Arthur Chatton
timpmorris.bsky.social
Great post here. Touches on so many interesting points about causal inference, estimands, development of methods, operator skill, etc. I encourage people who work on methods to read it!
@dingdingpeng.the100.ci
www.the100.ci/2024/04/13/i...
Is [insert statistical approach] good or bad? Let’s settle the debate, once and for all
I don’t like getting into fights and sometimes I am concerned this keeps me from becoming a proper methods/stats person. Getting into fights about one or multiple (or all) of the following just seems ...
www.the100.ci
April 23, 2024 at 4:42 PM
Reposted by Arthur Chatton
dingdingpeng.the100.ci
Do you think that learning more about causal inference is not worth it because you're running experiments anyway, or because you're interested in predictive questions? In that case, I've written a paper just for you, out now in SPPC: compass.onlinelibrary.wiley.com/doi/10.1111/...
Causal inference for psychologists who think that causal inference is not for them. Correlation does not imply causation and psychologists' causal inference training often focuses on the conclusion that therefore experiments are needed—without much consideration for the causal inference frameworks used elsewhere. This leaves researchers ill-equipped to solve inferential problems that they encounter in their work, leading to mistaken conclusions and incoherent statistical analyses. For a more systematic approach to causal inference, this article provides brief introductions to the potential outcomes framework—the “lingua franca” of causal inference—and to directed acyclic graphs, a graphical notation that makes it easier to systematically reason about complex causal situations. I then discuss two issues that may be of interest to researchers in social and personality psychology who think that formalized causal inference is of little relevance to their work. First, posttreatment bias:... DAG illustrating posttreatment bias which can be induced in randomized experiments whenever researchers condition on posttreatment variables Figure illustrating various reasons why demonstrations of incremental validity may be unimpressive: established predictors are omitted, measurement error is ignored, only little predictive utility is gained
March 2, 2024 at 5:25 AM