This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical
An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the bas
A daily glass of wine prolongs life—yet alcohol can cause life-threatening cancer. Some say raising the minimum wage will decrease inequality while others say
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is
One of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is