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      Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction

      2 in stock

      Firm sale: non returnable item
      SKU 9780521885881 Categories ,
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      This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
      Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if p...

      £49.99

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      Description

      Product ID:9780521885881
      Product Form:Hardback
      Country of Manufacture:US
      Title:Causal Inference for Statistics, Social, and Biomedical Sciences
      Subtitle:An Introduction
      Authors:Author: Donald B. Rubin, Guido W. Imbens
      Page Count:644
      Subjects:Economics of industrial organization, Economics of industrial organisation, Health economics, Epidemiology and Medical statistics, Probability and statistics, Health economics, Epidemiology & medical statistics, Probability & statistics
      Description:Select Guide Rating
      This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
      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.
      Imprint Name:Cambridge University Press
      Publisher Name:Cambridge University Press
      Country of Publication:GB
      Publishing Date:2015-04-06

      Additional information

      Weight1366 g
      Dimensions257 × 183 × 36 mm