My Simple Understanding of Total Effect = Direct Effect + Indirect Effect (via Mediator)

I’ve struggled with differentiating between total, direct, and indirect effects, so this blog/note serves as a personal reference to solidify my understanding and make future amendments as needed. While there are comprehensive articles available, this is a simplified explanation for myself and potentially others

My Coaching Notes: Effective Coaching

Effective coaching is essential for bringing the coachee’s potential to the surface. I found the 1-2-3-4 combination method to be helpful and have created a framework for myself to fall back on should I deviate from coaching questions. I plan to practice this framework iteratively and deliberately, listening for the trigger to ask a coaching question. Additionally, I found both books, ‘The Coaching Habit’ and ‘Developing Coaching Skills’, to be significantly helpful in crafting and adhering to the best practices of coaching questions.

My Coaching Notes: The Map - Navigating the Coaching Path

This year, I’m dedicated to improving my coaching skills by carefully selecting a few recommended books to guide my development. I plan to thoroughly read, re-read, and take detailed notes to distill their concepts and techniques into an easily accessible format. My goal is to use these insights on a daily basis to refine my coaching abilities iteratively.

Exploring Non-linear Effects: Visual CATE Analysis of Continuous Confounders, Binary Exposures, and Continuous Outcomes

It was enjoyable to visualize the non-linear relationship with interaction and observe the corresponding changes in CATE. If one understands the underlying equation, it’s possible to easily obtain the ATE using calculus. Lastly, adopting Richard McElreath’s Owl framework as a documented procedure ensures quality assurance! 🙌

Clearer Understanding of 95% Confidence Interval Through The Lens of Simulation

I’m now more confident in my understanding of the 95% confidence interval, but less certain about confidence intervals in general, knowing that we can’t be sure if our current interval includes the true population parameter. On a brighter note, if we have the correct confidence interval, it could still encompass the true parameter even when it’s not statistically significant. I find that quite refreshing