bookJul 16, 2009Closed access

Propensity Score Analysis: Statistical Methods and Applications

University of North Carolina at Chapel Hill

Abstract

List of Tables List of Figures Preface About the Authors Chapter 1: Introduction Observational Studies History and Development Randomized Experiments Why and When a Propensity Score Analysis Is Needed Computing Software Packages Plan of the Book Chapter 2: Counterfactual Framework and Assumptions Causality, Internal Validity, and Threats Counterfactuals and the Neyman-Rubin Counterfactual Framework The Ignorable Treatment Assignment Assumption The Stable Unit Treatment Value Assumption Methods for Estimating Treatment Effects The Underlying Logic of Statistical Inference Types of Treatment Effects Treatment Effect Heterogeneity Heckman's Econometric Model of Causality Conclusion Chapter 3: Conventional Methods…

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Topics & keywords

Keywords
  • Propensity score matching
  • Causal inference
  • Estimator
  • Computer science
  • Counterfactual thinking
  • Matching (statistics)
  • Econometrics
  • Weighting
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