Causality statistical perspectives and applications /

Table of 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.…”
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Causality models, reasoning, and inference / by Pearl, Judea

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Causality statistical perspectives and applications /

Table of 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.…”
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Causality models, reasoning, and inference / by Pearl, Judea

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Causality and Causal Modelling in the Social Sciences Measuring Variations / by Russo, Federica

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Skepticism, causality and skepticism about causality /

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Skepticism, causality and skepticism about causality /

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Causality and Causal Modelling in the Social Sciences Measuring Variations / by Russo, Federica

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Causal learning.

Development and Causality Neo-Piagetian Perspectives / by Young, Gerald

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Quantum Causality Conceptual Issues in the Causal Theory of Quantum Mechanics / by Riggs, Peter J.

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Mind and causality

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Causal models how people think about the world and its alternatives / by Sloman, Steven A.

Table of Contents: “…Agency and the role of causation in mental life -- The information is in the invariants -- What is a cause? -- Causal models -- Observation versus action -- Reasoning about causation -- Decision making via causal consequences -- The psychology of judgment : causality is pervasive -- Causality and conceptual structure -- Categorical induction -- Locating causal structure in language -- Causal learning -- Causation in the mind.…”
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Causal learning psychology, philosophy, and computation /

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Causality and connectives from Grice to relevance / by Bardzokas, Valandis

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Causality and motivation

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Substantiality and causality /

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Causality and connectives from Grice to relevance / by Bardzokas, Valandis

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Causality and motivation

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Substantiality and causality /

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