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Causal Inference for Statistics, Social, and Biomedical Sciences: An
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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction Hardcover - 2015 - 1st Edition

by Guido W. Imbens; Donald B. Rubin


From the publisher

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.

Details

  • Title Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
  • Author Guido W. Imbens; Donald B. Rubin
  • Binding Hardcover
  • Edition number 1st
  • Edition 1
  • Pages 644
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press, United States
  • Date 2015-04-06
  • Features Bibliography, Index
  • ISBN 9780521885881 / 0521885884
  • Weight 2.85 lbs (1.29 kg)
  • Dimensions 10 x 7.3 x 1.4 in (25.40 x 18.54 x 3.56 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Library of Congress subjects Social sciences - Research, Causation
  • Library of Congress Catalog Number 2014020988
  • Dewey Decimal Code 519.54
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