Joseph Bertrand - Wikipedia

Someone mentioned Bertrand in the recent discussion of DAGs and the Monty Hall problem. If you think yourself relatively smart, read his bio, chances are that, like me, you are a slowpoke in comparison
#DAG #causalinference

en.wikipedia.org/wiki/Joseph_...

"Introduction to Causal Inference" exposes participants to a wide range of tools used by modern social scientists to identify effects, including diff-in-diff, matching, regression discontinuities, synthetic controls, and more! For more info: myumi.ch/61WEj

#SumProg26 #ICPSR #CausalInference

CUPED: Old Wine in a New Bottle? CUPED has become a popular feature in online experimentation platforms. Regression works fine too.

Is CUPED just regression adjustment in disguise? You be the judge: nothing-so-practical.com/post/cuped-v...

#ABtest #experiment #CausalSky #Causalinference

Two common misconceptions when repurposing data for #causalinference:
1) the target trial is an ideal trial
2) the target trial protocol can be prespecified

Our new paper examines how the target trial protocol depends on the causal question AND the available data.

journals.lww.com/epidem/abstr...

Moving the field forward on moral injury: Possibilities and pitfalls of experimental research Research on Moral Injury (MI) is largely based on cross-sectional observational studies, mostly retrospective. Progress in understanding the causal me…

Get your free copy here 👇🏻:

www.sciencedirect.com/science/arti...

#MoralInjury #CausalInference

Generalizing Generalizability in Information Systems Research | Information Systems Research

#statstab #517 Generalizing Generalizability in Information Systems Research

Thoughts: Do your findings generalise? What does that mean?

#design #causalinference #theory #generalisability

pubsonline.informs.org/doi/10.1287/...

Causal Inference Is Hard How I learned to stop worrying and love assumptions

What makes #causalinference hard? It's not the math or the code: nothing-so-practical.com/post/causal-...

#CausalSky #ABtest

Causal Inference Is Easy An accessible approach to thinking about causal inference

DAGs and potential outcomes are useful frameworks but they miss some things that are helpful to understand in practice. #CausalInference is Easy: nothing-so-practical.com/post/causal-...

#cause #causal #PotentialOutcomes #DAG

Causal Inference in R Course | Online Training | Statistical Horizons Live online course on causal inference in R using matching and weighting methods to estimate the causal effect of a treatment on an outcome.

Join "Causal Inference in R Using MatchIt and WeightIt" with @noahgreifer.bsky.social on April 15-17. Gain hands-on #causalinference experience in #Rstats and learn matching and weighting methods for estimating and interpreting treatment effects.

I Built an Agent That Refuses to Say "Causes" Coding agents confidently say "X causes Y" without drawing a DAG, checking assumptions, or running refutation tests. I built an Agent Skill that won't let them. 100% eval pass rate vs 68% without -- t...

Wrote up the full story behind the #CausalInference agent skill.
Key insight: agents *know* causal inference, but they never stop to ask "is my DAG right?" or "does this survive a placebo test?"

The skill doesn't add knowledge. It adds discipline.
Full breakdown: learnbayesstats.com/blog-posts/c...

Ready to move beyond correlations? Join Andrew Li for "Causal Mediation Analysis" at the MethodsNET Summer School with CEU. Master the algorithms to unpack causal mechanisms in your research.

📍 Vienna | June 2026
🔗 methodsnet.org/course/d03-c...
#MethodsNET #CausalInference #AcademicSky

New episode is out, my dear Bayesians! All about #CausalInference, #Experimentation at scale, and #GaussianProcesses -- definitely a fun one!

Bayesian Causal Inference at Scale Thomas Pinder discusses Bayesian causal inference and Gaussian processes. Explore synthetic control and diff-in-diff for industry

New Episode Alert!
🎙️ Scaling #BayesianCausalInference with Thomas Pinder, Netflix & creator of GPJax

Essential listening for anyone working at the frontier of Bayes, Experimentation & Causal Inference 📈
🔗 learnbayesstats.com/episode/154-...

#Bayesian #JAX #MachineLearning #CausalInference #GPJax

Original post on hachyderm.io

"Five skills. Each one is counter-cyclical (becomes more valuable as hype recedes), resistant to LLM automation (requires human judgment that pattern-matching can’t replicate), and directly tied to the business outcomes executives actually pay for."
by Kaushik Rajan […]

Apply now: T32 Postdoctoral Research Fellow

Searching for a postdoc opportunity?

CAUSALab is reviewing applications for the T32 Training Program in Comparative Effectiveness Research for Suicide Prevention (Funded by NIMH, T32 MH125815).

🔗 Apply:
form.jotform.com/201476846966...

Learn more in comments. #causalinference

Graph Neural Networks can help reveal causal relationships in marine systems.

ecotwinproject.eu/post/graph-n...

#EcoTwin #AI #CausalInference #DigitalTwins

Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework Synthetic control (SC) methods are commonly used to estimate the treatment effect on a single treated unit in panel data settings. An SC is a weighted average of control units built to match the tr...

www.tandfonline.com/doi/full/10....

#causalsky #causalinference #StatsSky

Individualized Dynamic Mediation Analysis Using Latent Factor Models Mediation analysis plays a crucial role in causal inference as it can investigate the pathways through which treatment influences outcome. Most existing mediation analysis assumes that mediation ef...

www.tandfonline.com/doi/full/10....

#CausalSky #causalinference #statssky

Causal Inference Certification | Causal Training | Statistical Horizons Causal inference certification for researchers seeking applied training & a credential in causal methods. Complete four live online seminars.

Get certified in #causalinference. Across 4 seminars, you’ll learn how to think more clearly about design, estimation, assumptions, and interpretation in applied settings. Strengthen your research toolkit and earn a credential in the process.

Online course on Causal Inference using an SEM Approach from June 1-5, 2026 with registration link.

Ready to level up your research skills? 🚀 "Causal Inference: An SEM Approach" covers #CausalInference, #PathAnalysis, #SEMs, and #Econometrics—all in one workshop! Sign up now: myumi.ch/158dw

#SumProg26 #ICPSR #GraduateStudies #ProfessionalDevelopment #ResearchSkills

Causal Inference in R Course | Online Training | Statistical Horizons Live online course on causal inference in R using matching and weighting methods to estimate the causal effect of a treatment on an outcome.

Looking to strengthen your #causalinference skills? Join @noahgreifer.bsky.social on April 15-17 for "Causal Inference in R Using MatchIt and WeightIt" to gain the skills to apply these #Rstats packages to estimate and interpret treatment effects.

Rule 🥇: temporal leakage is a sin. You don't use the future to forecast the past.
Rule 🥈: don’t forecast what you can measure.
Rule 🥉: counterfactuals don’t get spoilers. If it knows what happened next, it's not a counterfactual. It’s fanfiction.
#forecasting #causalinference #mlsky

Key Topics in Causal Inference (KTCI). Dates: June 8-12, 2026. Taught by Miguel Hernán, Sara Lodi, Judith Lok, James Robins, Eric Tchetgen Tchetgen & Tyler VanderWeele

Want to build a foundation of #causalinference methodology?

Key Topics in Causal Inference (KTCI) is for researchers interested in acquiring a roadmap to the current causal research landscape.

📆 June 8-12, 2026
📍 In-person @hsph.harvard.edu / online

Learn more:
hsph.harvard.edu/research/cau...

The effect of SARS-CoV-2 testing on healthcare-seeking behaviour at primary care level AbstractBackground. Diagnostic self-testing for SARS-CoV-2 may lead to selection bias in test-negative case–control designs (TND) for COVID-19 vaccine effe

academic.oup.com/ije/article/...

#EpiSky #COVID19 #CausalSky #causalinference

07 - Beyond Confounders — Causal Inference for the Brave and True

#statstab #505 Beyond Confounders

Thoughts: What makes a good control and a bad control?

#counterfactuals #confounder #DAG #r #modelling #selectionbias #variance #control #causalinference

matheusfacure.github.io/python-causa...

Humans in the Loop: The Next Frontier in the Credibility Revolution Something is amiss in empirical economics. Despite the advances of the credibility revolution, published estimates tend to be inflated and overconfident. We arg

Paper link here! 13/13
papers.ssrn.com/sol3/papers....

#econsky #polisky #MetaScience #OpenScience #CausalInference #StatsTwitter #Econometrics #AcademicSky

Target Trial Emulation (TTE). Dates: June 8-12, 2026. Taught by Barbra Dickerman, Joy Shi, Miguel Hernán

Interested in using health databases for #causalinference research?

Target Trial Emulation (TTE) covers the target trial emulation framework in increasingly complex settings.

📆 June 8-12, 2026

Taught by Babra Dickerman, Joy Shi, @miguelhernan.org

Apply now:
hsph.harvard.edu/research/cau...

Debiased Front-Door Learners for Heterogeneous Effects In observational settings where treatment and outcome share unmeasured confounders but an observed mediator remains unconfounded, the front-door (FD) adjustment identifies causal effects through the m...

Our paper “Debiased Front-Door Learners for Heterogeneous Effects” was accepted to ICLR 2026.

- Paper (arXiv): arxiv.org/abs/2509.22531
- Reproducible code: github.com/yonghanjung/...

Quick start:
pip install fd-cate
fdcate demo --outdir ./fdcate-demo
#ICLR2026 #CausalInference #MachineLearning

Most quant models are correlational - they tell you what moved together in the past.

But robust investing needs more than correlation. It needs causal structure + functional form.

Our latest blog explores how the two work together.

👉 Read more: dub.link/Xe9cHWg

#CausalInference #QuantFinance

Does anyone out there have a syllabus for a causal inference course targeting senior undergrad or early grad students? ##AcademicSky #CausalInference