Publications by r on Everyday Is A School Day
Gemini 1.5 Flash Better Than RAG? Let’s Check It Out In R!
Overall, I am quite impressed with the responses! With minimal prompt engineering, document cleaning! It was able to return accurate responses, and even separated different conditions and provided appropriate treatment options. It was also able to return the correct response for tricky questions that our RAG was not able to. It definitely has poten...
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Llama, Llama, Oh Give Me A Sign. What’s In The Latest IDSA Guideline?
Wow, what a journey, and more to come! We learned how to perform simple RAG with an LLM and even ventured into LangChain territory. It wasn’t as scary as some people said! The documentation is fantastic. Best of all, we did it ALL in R with Reticulate, without leaving RStudio! Not only we can read IDSA Guidelines, we can use LLM to assist us with...
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V_s__l_ng M_ss_ng D_t_ W_th D_G & S_m_l_t__n
MCAR, MAR, MNAR, all so confusing. But with DAG, oh so amusing! Many technical words, I don’t understand, but with simulation, I am a fan! Join me in exploring missing mechanisms, learn I will with great optimism. Visualizing Missing Data With DAG & Simulation Just for kicks, what is the missing mechanism of the title? Scroll all t...
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S.P.I.C.E of Causal Inference
The SUTVA, Positivity, Identifiability, Consistency, Exchangeability of Causal Inference, the essential ingredients that helps us bring out the true flavor of the causal model. Here is my understanding of each assumptions (main course) with examples (side dish) and accompanied by simulation (paired with beverages). Bon Appétit! Since the multiple...
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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 Objectives Reason For This Note ...
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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! 🙌 Question of the...
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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�...
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An Educational Stroll With Stan – Part 4
What an incredible journey it has been! I’m thoroughly enjoying working with Stan codes, even though I don’t yet grasp all the intricacies. We’ve already tackled simple linear and logistic regressions and delved into the application of Bayes’ theorem. Now, let’s turn our attention to the fascinating world of Mixed-Effect Models, also know...
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An Educational Stroll With Stan – Part 3
Diving into this, we’re exploring how using numbers to express our certainty, especially with medical results, can help sharpen our estimated ‘posterior value’ and offer a solid base for learning and discussions. We often talk about specifics like sensitivity without the nitty-gritty math, but crafting our own priors and using a dash of Bayes...
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An Educational Stroll With Stan – Part 2
I learned a great deal throughout this journey. In the second part, I gained knowledge about implementing logistic regression in Stan. I also learned the significance of data type declarations for obtaining accurate estimates, how to use posterior to predict new data, and what generated quantities in Stan is for. Moreover, having a friend who is we...
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