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 ...

Causal Inference in Quantitative Trading: The Pitfalls of Correlation, Counterfactuals, and Identifying True Alpha

Discovering variables that can predict future returns is an important step in quantitative trading research.However, it is ...
BIOENGINEER

Causal Inference Boosts Privacy-Preserving Federated Learning Across Organizations

A Scientific Reports study presents a causal-enhanced federated transfer learning framework that improved cross-domain ...
umass

Corwin Zigler: Bayesian Causal Inference with Uncertain Physical Process Interference

Abstract: Causal inference with spatial environmental data is often challenging due to the presence of interference: outcomes for observational units depend on some combination of local and non-local ...
umass

Do observational causal inference methods really work?

Over the past several decades, multiple statistical methods have been developed to infer the existence and magnitude of causal effects by analyzing observational data. These methods have been widely ...
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 ...

Revealed by Statistical Causal Inference: Is Energy Regulation Really a 'Hindrance'?

"Because of regulations, our company was 10 years late to solar power"—an executive at a major power company laments. However ...
JSTOR Daily

Causality In Crisis?: Statistical Methods & Search for Causal Knowledge in Social Sciences

Your institution does not have access to this book on JSTOR. Try searching on JSTOR for other items related to this book. https://doi.org/10.2307/jj.21995551.4 https ...