Counterfactuals and Causal Inference
Stephen L. Morgan · 2007 · 414 pages
As an Amazon Associate we earn from qualifying purchases. Some book links are affiliate links; you pay the same price and we may earn a small commission.
About this book
"In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed"--
Appears in these reading paths
Best Books to Learn Political Science, in Order
Related reading guides
Reader reviews
Ratings and notes from readers — tagged with how deep into the subject they were.
Loading reviews…