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Causality : statistical perspectives and applications / Carlo Berzuini, Philip Dawid, Luisa Bernardinelli.

By: Contributor(s): Material type: TextTextSeries: Wiley series in probability and statisticsPublication details: Hoboken, N.J. : Wiley, 2012.Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119941736
  • 1119941733
  • 9781119945703
  • 1119945704
  • 9781119941743
  • 1119941741
  • 9781119945710
  • 1119945712
  • 0470665564
  • 9780470665565
Subject(s): Genre/Form: Additional physical formats: Print version:: Causality.DDC classification:
  • 519.5/44 23
LOC classification:
  • QA276.8
Other classification:
  • MAT029000
Online resources:
Contents:
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.
Summary: "This book looks at a broad collection of contributions from experts in their fields"-- Provided by publisher.
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"This book looks at a broad collection of contributions from experts in their fields"-- Provided by publisher.

Includes bibliographical references and index.

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.

Print version record and CIP data provided by publisher.

Social Sciences and Humanities