Causal Inference in Statistics A Primer.

Detalles Bibliográficos
Autor principal: Pearl, Judea
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2016.
Colección:New York Academy of Sciences Ser.
Temas:
Electronic books.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright
  • Dedication
  • Table of Contents
  • About the Authors
  • Preface
  • Acknowledgments
  • List of Figures
  • About the Companion Website
  • Chapter 1: Preliminaries: Statistical and Causal Models
  • 1.1 Why Study Causation
  • 1.2 Simpson's Paradox
  • 1.3 Probability and Statistics
  • 1.4 Graphs
  • 1.5 Structural Causal Models
  • Bibliographical Notes for Chapter 1
  • Chapter 2: Graphical Models and Their Applications
  • 2.1 Connecting Models to Data
  • 2.2 Chains and Forks
  • 2.3 Colliders
  • 2.4 d-separation
  • 2.5 Model Testing and Causal Search
  • Bibliographical Notes for Chapter 2
  • Chapter 3: The Effects of Interventions
  • 3.1 Interventions
  • 3.2 The Adjustment Formula
  • 3.3 The Backdoor Criterion
  • 3.4 The Front-Door Criterion
  • 3.5 Conditional Interventions and Covariate-Specific Effects
  • 3.6 Inverse Probability Weighing
  • 3.7 Mediation
  • 3.8 Causal Inference in Linear Systems
  • Bibliographical Notes for Chapter 3
  • Chapter 4: Counterfactuals and Their Applications
  • 4.1 Counterfactuals
  • 4.2 Defining and Computing Counterfactuals
  • 4.3 Nondeterministic Counterfactuals
  • 4.4 Practical Uses of Counterfactuals
  • 4.5 Mathematical Tool Kits for Attribution and Mediation
  • Bibliographical Notes for Chapter 4
  • References
  • Index
  • End User License Agreement

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