Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science.
- Provides a clear account and comparison of formal languages, concepts and models for statistical causality.
- Addresses examples from medicine, biology, economics and political science to aid the reader's understanding.
- Is authored by leading experts in their field.
- Is written in an accessible style.
Postgraduates, professional statisticians and researchers in academia and industry will benefit from this book.
Keywords: R, STATA, SAS, Causal inference, causal relationship, cause effect statistics, statistical causality, Causal inference, statistics, Bayesian Analysis, Applied Probability & Statistics - Models, Bayesian Analysis, Applied Probability & Statistics - Models