This repository contains a Jupyter notebook that explores the concept of confounding variables in causal inference. The notebook provides both theoretical explanations and practical coding examples to ...

School of Mathematics and System Sciences, Beihang University, Beijing, China. Causal inference has become an important research field in statistics, data mining, epidemiology and machine learning etc ...

Confounding of three binary-variable counterfactual model with directed acyclic graph (DAG) is discussed in this paper. According to the effect between the control variable and the covariate variable, ...

This report aims to provide methodological guidance to help practitioners select the most appropriate weighting method based on propensity scores for their analysis out of many available options (eg, ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

It is established that pleiotropic effects of common genetic variants can substantially confound epidemiologic association studies. However, existing approach adjusting for genetic confounding mostly ...