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 variable - explanatory article ===== A confounding variable (or confounder) is an unmeasured third variable in a study that influences both the supposed cause (independent variable) and ...

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 ...

In Business Intelligence (BI), recognizing and mitigating the impact of confounding variables is crucial for accurate data analysis. Confounding variables are factors other than the independent ...

ROUNDS_PER_EVALUATION=50 # number of rounds to evaluate the online planning and policy execution, for each evaluation EVALUATIONS=1 # number of independent ...