Phys.org

Statistical tools for valid causal inference with fewer assumptions

Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference ...
BMJ

Causal inference in physical activity epidemiology research: an opportunity for better evidence

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
lse

Causal Inference for Observational and Experimental Studies

This course is available on the MSc in Applied Social Data Science, MSc in Behavioural Science, MSc in Human Geography and Urban Studies (Research), MSc in Innovation Policy, MSc in International ...
CU Boulder News & Events

Causal Inference and COVID: Contrasting Methods for Evaluating Pandemic Impacts Using State Assessments

This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score ...
Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Informationsdienst Wissenschaft

New Department "Computational Precision Nutrition" at DIfE

On July 1, 2026, the new department "Computational Precision Nutrition" commenced its research activities at the German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), led by Prof. Stefan ...
lse

Causal Inference for Observational and Experimental Studies

This course is available on the MPhil/PhD in Economic Geography, MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in Regional and Urban Planning Studies, MRes in ...