This book looks at a broad collection of contributions from experts in their fields. Providing a thorough treatment on statistical causality. Methods and their applications are provided with theoretical background and emphasis is given to practice rather than theory, with technical content kept to a minimum. Step-by-step instructions for using the methods are presented with a broad range of examples, including medicine, biology, economics, sociology and political science.
Preface (editors) 1 Statistical Causality: Some Historical Remarks AUTHOR(S): D.R. Cox 2 The Language of Potential Outcomes AUTHOR(S): Arvid Sjolander 3 Structural Equations, Graphs and Interventions AUTHOR(S): Ilya Shpitser 4 The Decision-Theoretic Approach to Causal Inference AUTHOR(S): A. Philip Dawid 5 Causal Inference as a Prediction Problem: Assumptions, Identification, and Evidence Synthesis AUTHOR(S): Sander Greenland 6 Graph-Based Criteria of Identifiability of Causal Questions AUTHOR(S): Ilya Shpitser 7 Causal inference from observational data: a Bayesian predictive approach AUTHOR(S): Elja Arjas 8 Causal Inference from Observing Sequences of Actions 9 Causal Effects and Natural Laws: towards a Conceptualization of Causal Counterfactuals for Non-Manipulable Exposures, with Application to the Effects of Race and Sex AUTHOR(S): Tyler J. VanderWeele and Miguel A. Hernan 10 Cross-Classifications by Joint Potential Outcomes AUTHOR(S): Arvid Sjolander 11 Estimation of Direct and Indirect Effects AUTHOR(S): Stijn Vansteelandt 12 The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models AUTHOR(S): Judea Pearl 13 The Sufficient Cause Framework in Statistics, Philosophy and the Biomedical and Social Sciences AUTHOR(S): Tyler J. VanderWeele 14 Inference about Biological Mechanism on the Basis of Epidemiological Data AUTHOR(S): Carlo Berzuini and A. Philip Dawid 15 Ion Channels and Multiple Sclerosis AUTHOR(S): Luisa Bernardinelli, Carlo Berzuini, Luisa Foco and Roberta Pastorino 16 Supplementary Variables For Causal Estimation AUTHOR(S): Roland R. Ramsahai 17 Time-Varying Confounding: Some Practical Considerations in a Likelihood Framework AUTHOR(S): Rhian Daniel, Bianca De Stavola and Simon Cousens 18 Natural Experiments as a Means of Testing Causal Inferences AUTHOR(S): Michael Rutter 19 Nonreactive and Purely Reactive Doses in Observational Studies AUTHOR(S): Paul R. Rosenbaum 20 Evaluation of PotentialMediators in Randomized Trials of Complex Interventions(Psychotherapies) AUTHOR(S): Richard Emsley and Graham Dunn 21 Causal Inference in Clinical Trials AUTHOR(S): Krista Fischer and Ian R. White 22 Granger Causality and Causal Inference in Time Series Analysis AUTHOR(S): Michael Eichler 23 Dynamic Molecular Networks and Mechanisms in the Biosciences: A Statistical Framework AUTHOR(S): Clive G. Bowsher Index