The application of causal inference methods is growing exponentially in fields that deal with observational data. Written by pioneers in the field, this practic

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is

An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the bas

This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical

The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hun