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- Causal Inference in Action: Discord Clubs, Case Studies with Code, SEM Live Deep-Dive, New Book Releases, and more🎁
Causal Inference in Action: Discord Clubs, Case Studies with Code, SEM Live Deep-Dive, New Book Releases, and more🎁
Explore the latest in causal inference. Collaborate, learn, and grow with thousands of fellow learners.
Justin Belair
July 07, 2025
Dear Causal Inference in Biostatistics Enthusiast,
[BOOK] Three (3) Chapters from my Causal Inference Book Available Soon—including case-study code notebooks
I’m currently wrapping up Chapter 4 — Removing Confounding and Propensity Score Methods—, Chapter 5 —The Art of Observational Studies: Pragmatically Bridging Causal Frameworks—, and Chapter 7—Quasi-Experimental Designs: Simulated Randomness.
Check this out:
Chapter 4 Case-Study: a famous study of Right Hearth Catheterization. The original study did not visualize the data and used outdated Propensity Score Methods — we will remedy this together!
The case-study code-notebooks in these Chapters are easily the best I wrote so far!
If you pre-order my Causal Inference in Statistics, with Exercises, Practice Projects, and R Code Notebooks, you now receive
A 158 page PDF with the first 3 chapters
5 R code notebooks
Receive the new parts of the book upon release (3 new chapters + 6 additional notebooks, coming soon) and any updates to the material via Github
A pre-order for the full book once it is complete
You can order now - You will be the first to receive the new material when it launches 😋
What's The Plan?
[LIVE Event] Structure Meets Causality: Structural Equation Models, A Deep Dive
Dr. Christian Geiser is a world-renown leader of Causality in SEM, and runs a successful statistics education platform Quantfish.
What You’ll Learn:
How causality and SEM are related, common myths about SEM, and more.
Tools and resources, for beginners and pros, about Causality and SEM
Your questions answered LIVE!
Have a question for us? Send it in now by replying to this message, and we will feature it live!
When? July 16, 2025 🕛 12 PM Eastern Time
Who? Speakers: Justin Belair & Dr. Christian Geiser
How? Click below to reserve your spot!
[DISCORD] Causal Inference Journal Club + Book Club 🤓
Whether you're a student, researcher, practitioner, or just curious, this is a great place to:
📖 Discuss important papers or books
💬 Ask and answer questions
🧪 Share resources and code
🌍 Connect with like-minded peers
Journal Club #2
When: July 9, 10:30AM Eastern Time
Topic: Can we trust observational data? Keeping bias in mind
Book Club #1
When: July 23, 11:00AM Eastern Time
Topic: The Art of Statistics, by David Spieghalter
Once in the Discord ➡️ voice channels ➡️ journal-club or book-club, the events will be held there!
[COURSE] Introduction to Biostatistics — Exclusive Discount
Aleksander Molak and I have finished the Founding Cohort. They gave us amazing feedback and insights into making this course exceptional. We are working to produce the self-paced online version as you read this! Our students loved it, and this touches our hearts 💜
📊 For anyone interested in statistics, especially causal inference, I just finished a cohort course with Justin Bélair and Aleksander Molak and it was 🔥. I highly recommend them. They are the best course creators I’ve met. They mix statistics with philosophy and use thought experiments to teach. They genuinely care about feedback and encourage real discussion.
[Case-Study] Don’t Drop Non-Significant Interactions From Your Model
Recently, a client suggested we just drop non-significant interactions from the model, despite the split-plot design naturally flowing into a model of the interactions. Below is how I responded. The client agreed, and we used a better and more statistically sound approach.
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If you need help with statistics, reach out for a free 30-minute discovery call.
Chapter 9 of my upcoming book will be all about interpretation of interaction (or moderation) effects, and mediation analysis—two topics that benefited tremendously from our advanced understanding of causality.
Best Causal Inference Books with Reviews | The Full List
Overwhelmed by the rapidly expanding causal inference material, we got you covered with books by Pearl, Rubin, and other leading causal inference researchers!
biostatistics.ca Launched a Newsletter and a FREE Github library with code
We’re expanding out content: to weekly articles, we now added a newsletter and free repository to share code notebooks!
I Featured On A Podcast!
Thanks to Venkat Raman from Aryma labs for inviting me on his great Casual Causal Talk podcast — we discussed how I got started with Causal Inference, schools of thought in Causal Inference, Predictions vs Causality, Causal Discovery vs Inference, Causality in LLMs, and more.
Oh, and by the way, I’m reviving my Youtube Channel. There, you can find my live talks with Robert Rachford (x2), Darko Medin (x2), Mark Anderson, stats tutorials, and more—check it out!
biostatistics.ca Collaborations and Partnerships
Become a writer.
What’s in it for you?
You showcase your expertise, including a short author profile and a link of your choice.
Our website gets 1k+ clicks a month—this is a great way to drive traffic to a link of your choice and we share your article on Linkedin, where you can expect anywhere from 30 to 200 clicks, depending on the topic.
Become an official partner - Career experts, educational orientation services, product-vendors in the biostatistics space, consultants, educational content creators, and more.
What’s in if for you?
We write a blog about your offerings on our website (expect around 30-200 clicks in the first week). This also creates a backlink to a fast growing website (over 10x traffic in under a year).
We drive leads to your services.
Check out our new partnerships with Adoc Talent Management, Easy-Statistik, AInovate, MarketEdge, and JB Statistical Consulting!
Interested? Email [email protected] or send me a DM!
Consulting
Here's what a Lead R&D scientist in biotech, Victor Kang, whom I’ve collaborated with for over a year had to say:
" [...] Immediately from our first call, Justin stood out from other candidates that I have considered: he was highly knowledgeable about the underlying theory behind various statistical approaches, and he could clearly explain when and why I should use them. Furthermore, he was unique in appreciating the need to balance academic rigour with the realities of running biological field trials (i.e., uncontrollable variables, time, cost).[...] I have learned much theory and practice from him, and our collaborations have resulted in real business impact. [...] I look forward to continuing our collaboration!"
Ready to discuss how I can help?
Until next time.
thestatsnerd,
Justin
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