Fundamentals of causal inference : with R
著者
書誌事項
Fundamentals of causal inference : with R
（Texts in statistical science）
CRC Press, 2022
- : hbk
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注記
Includes bibliographical references (p. 225-231) and index
内容説明・目次
内容説明
Requires minimal prerequisites
Explained in basic terms
Illustrated with binary datasets and real life examples
Covers primary concepts and methods
Accessible to undergraduates
Suitable for a heterogeneous audience
目次
1. Introduction. 2. Conditional Probability and Expectation. 3. Potential Outcomes and the Fundamental Problem of Causal Inference. 4. Effect-measure Modification and Causal Interaction. 5. Causal Directed Acyclic Graphs. 6. Adjusting for Confounding: Back-door method via Standardization. 7. Adjusting for Confounding: Difference-in-Differences Estimators. 8. Adjusting for Confounding: Front-door method. 9. Adjusting for Confounding: Instrumental Variables. 10. Adjusting for Confounding: Propensity-score Methods. 11. Efficiency with Precision Variables. 12. Mediation.
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