The estimand framework, formalized in ICH E9(R1) regulatory guidance, provides a structured approach to define scientific objectives with precision. We apply the estimand framework to dose–exposure–response analyses. ... strategy to improve exposure–response analyses for dose selection, particularly when the relevant evidence includes data from multiple studies.

#estimand #exposure-response #dose-response #causal #pharmacometrics #pmx

https://doi.org/10.1002/psp4.70202

The vast datasets on which LLMs are trained are repositories of human linguistic activity, imbued with the collective referential histories of countless speakers. Even if an #LLM does not "know" these histories in a human-like conscious sense, the statistical patterns it learns from this data implicitly encode these #causal-historical links.

https://jordivitria.substack.com/p/meaningful-language-understanding

fly51fly (@fly51fly)

에피스템릭 후회 최소화(Epistemic Regret Minimization)를 제안해 LLM에서 발생하는 인과적 'rung collapse' 문제를 다룬 연구입니다. 모델이 '잘못된 이유로 정답을 선택'하는 현상을 진단하고 이를 완화하기 위한 알고리즘적 접근과 이론적 근거를 제시합니다.

https://x.com/fly51fly/status/2022427961300070680

#llm #causal #regretminimization #research

#statstab #482 Introducing Causion: A web app for playing with DAGs

Thoughts: A very cool app. Let's you see exactly what your assumptions and DGP mean for your causal model.

#causal #causalinference #DAG #DAGs #dgp #tutorial #guide #education #pedagogy

https://pedermisager.org/blog/causion-dag-simulator/

#statstab #476 Experimental : causal

Thoughts: Randomized experiments are the gold standard for inference for a reason. But they are hard to design.

#design #r #statistics #methods #experiment #tutorial #pedagogy #education #hypothesis #nhst #causal #ancova

https://book.declaredesign.org/library/experimental-causal.html

From the @DSLC ​chives:

 ISLR: Deep Learning https://youtu.be/1D6plTaDvTU #RStats

 The Effect: An Introduction to Research Design and Causality: Finding Front Doors https://youtu.be/8RJxoOz2dyg #RStats #causal #causality

 Geocomputation w R: Statistical learning & Ecology https://youtu.be/ozXzmWtv1_g #geocomputation #RStats

Support the Data Science Learning Community at https://patreon.com/DSLC

From the @DSLC ​chives:

 Bayes Rules! Posterior Inference & Prediction https://youtu.be/5U19BRPwPrs #RStats

 Modelado Tidy con R - 5. Gastando nuestros datos https://youtu.be/_E_5pBFtSJk #RStats

 The Effect: Treatment Effects & Causality with Less Modeling https://youtu.be/G3Ur3lZAYCs #RStats #causal #causality

Support the Data Science Learning Community at https://patreon.com/DSLC

Meta buried 'causal' evidence of social media harm, US court filings allege

https://www.reuters.com/sustainability/boards-policy-regulation/meta-buried-causal-evidence-social-media-harm-us-court-filings-allege-2025-11-23/

#HackerNews #Meta #Causal #Evidence #SocialMedia #Harm #CourtFilings #News