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 ...

We all follow the scientific method in one way or another, perhaps without even knowing it! How often have you become faced with a problem and then come up with a solution, only to have your plans ...

Anticipating the direction of a confounding variable can be problematic especially to introductory students. Using elementary rules of mathematics, we describe below a simple instructional tool for ...

Objectives To adjust for confounding in observational data, researchers use propensity score matching (PSM), but more advanced methods might be required when dealing with longitudinal data and ...