Counterfactuals and Causal Inference

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.

Author: Stephen L. Morgan, Christopher Winship
Publisher: Cambridge University Press
Published: 11/01/2014
Pages: 524
Binding Type: Hardcover
Weight: 2.40lbs
Size: 10.00h x 7.10w x 1.30d
ISBN13: 9781107065079
ISBN10: 1107065070
BISAC Categories:
- Social Science | Research
- Social Science | Methodology
- Mathematics | Probability & Statistics | General