Causality statistical perspectives and applications /

"This book looks at a broad collection of contributions from experts in their fields"--

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Dades bibliogràfiques
Autor corporatiu: ebrary, Inc
Altres autors: Berzuini, Carlo, Dawid, Philip, Bernardinelli, Luisa
Format: Electrònic eBook
Idioma:anglès
Publicat: Chichester, West Sussex, U.K. : Wiley, 2012.
Col·lecció:Wiley series in probability and statistics.
Matèries:
Accés en línia:An electronic book accessible through the World Wide Web; click to view
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Taula de continguts:
  • Statistical causality : some historical remarks
  • The language of potential outcomes
  • Structural equations, graphs and interventions
  • The decision-theoretic approach to causal
  • Causal inference as a prediction problem : assumptions, identification, and evidence synthesis
  • Graph-based criteria of identifiability of causal questions
  • Causal inference from observational data : a Bayesian predictive approach
  • Causal inference from observing sequences of actions
  • Causal effects and natural laws : towards a conceptualization of causal counterfactuals
  • For non-manipulable exposures, with application to the effects of race and sex
  • Cross-classifications by joint potential outcomes
  • Estimation of direct and indirect effects
  • The mediation formula : a guide to the assessment of causal pathways in nonlinear models
  • The sufficient cause framework in statistics, philosophy and the biomedical and social sciences
  • Inference about biological mechanism on the basis of epidemiological data
  • Ion channels and multiple sclerosis
  • Supplementary variables for causal estimation
  • Time-varying confounding : some practical considerations in a likelihood framework
  • Natural experiments as a means of testing causal inferences
  • Nonreactive and purely reactive doses in observational studies
  • Evaluation of potential mediators in randomized trials of complex interventions (psychotherapies)
  • Causal inference in clinical trials
  • Granger causality and causal inference in time series analysis
  • Dynamic molecular networks and mechanisms iIn the biosciences : a statistical framework.