CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we

This book is intended for anyone, regardless of discipline, who is interested in the use of statistical methods to help obtain scientific explanations or to pre

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

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

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