Join Us for a LinkedIn Live on Power Calculation + Announcing My New Book (And More Treats Inside!)

Dear Causal Inference in Biostatistics Enthusiast,

It’s Power Calculation and Sample Size Estimation Month! 🤓

Here’s the plan:

1. Free event announcement

2. Loads of resources to help you in your research!

3. Announcement for my new Causal Inference book

4. Other Resources

Linkedin Live Podcast

• What? Power Calculation and Sample Size Determination, from Basic to Complex Cases

• When? Wednesday, November 20, 12-1PM EDT

• Who? Justin Belair of JB Statistical Consulting and Robert Rachford of Better Biostats

• Q&A session at the end - my favorite part!

Prepare for the Live Session - Recommended Reading : Why should you care?

Free Downloads Alert 🚨

5 Misconceptions Around Statistical Power and Sample Size Estimation (Nobody talks about the last one) + R Markdown Coding Notebook to Try It Yourself

The last misconception is covered in a free practice exercise on Github :

📕Causal Inference in Statistics: with Exercises, Practice Projects, and R Code Notebooks

My new book is now available for pre-order!

Each chapter contains:

• loads of exercices

• free code notebooks with case studies for applied practice

• a suggested advanced project.

Here's my plan for the release, I have around 160 pages written and I'm wrapping up Chapter 3:

1. (ASAP) Release intro chapter for free (I'm really proud of it!)

2. (~ early 2025) Release Part I - Fundamentals of Causal Inference - 4 Chapters - ~200pages :

   • Chapter 1 - Intro

   • Chapter 2 - Fundamentals of Potential Outcomes

   • Chapter 3 - Graphical Causal Models

   • Chapter 4 - Observational Studies - Design and Analysis

3. (~ mid 2025) Release Part II - 5 Chapters - The Causal Inference Toolkit - ~200pages :

   • Chapter 5 - Removing Confounding and Propensity Score Methods

   • Chapter 6 - Instrumental Variable Methods

   • Chapter 7 - Structural Equation Models and Path Analysis

   • Chapter 8 - Methods for Mediation and Interaction

   • Chapter 9 - Quasi-Experimental Designs

4. (~ end 2025) Release Part III - 3 Chapters - Advanced Causal Inference - ~200pages :

   • Chapter 10 - Longitudinal Causal Inference

   • Chapter 11 - Machine Learning and Causal AI

   • Chapter 12 - Conclusion and Next Steps

I plan on working like this:

You buy it once, and you get everything free that comes out with the book, forever.

I think it's the start of something big for me :)

PS. If you'd like to read it (for free) against feedback, DM me and we can see what we can do!

Ready to purchase it?

Need help with stats? Let’s Talk!

I’m Justin Belair – an international expert on data science and statistics. My statistical consulting and freelance work have helped researchers from all over the world understand their data.

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