Causality statistical perspectives and applications /
"This book looks at a broad collection of contributions from experts in their fields"--
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| 団体著者: | |
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| その他の著者: | , , |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Chichester, West Sussex, U.K. :
Wiley,
2012.
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| シリーズ: | Wiley series in probability and statistics.
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| 主題: | |
| オンライン･アクセス: | An electronic book accessible through the World Wide Web; click to view |
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目次:
- 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.