Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives (Wiley Series in Probability and Statistics)

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives (Wiley Series in Probability and Statistics)

Andrew Gelman


This book brings jointly a collection of articles on statistical tools when it comes to lacking information research, together with a number of imputation, propensity ratings, instrumental variables, and Bayesian inference. protecting new learn subject matters and real-world examples which don't function in lots of common texts. The e-book is devoted to Professor Don Rubin (Harvard). Don Rubin  has made basic contributions to the research of lacking information.

Key positive factors of the e-book include:

  • Comprehensive insurance of an imporant sector for either examine and applications.
  • Adopts a practical method of describing a variety of intermediate and complicated statistical techniques.
  • Covers key themes corresponding to a number of imputation, propensity rankings, instrumental variables and Bayesian inference.
  • Includes a few purposes from the social and future health sciences.
  • Edited and authored through hugely revered researchers within the area.

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