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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Guido W. Imbens, Donald B. Rubin你有多喜歡這本書?
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Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
類別:
年:
2015
版本:
1st
出版商:
Cambridge University Press
語言:
english
頁數:
644
ISBN 10:
0521885884
ISBN 13:
9780521885881
文件:
PDF, 7.52 MB
你的標籤:
IPFS:
CID , CID Blake2b
english, 2015
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