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Fundamentals of Causal Inference
With R
Buch von Babette A. Brumback
Sprache: Englisch

86,35 €*

inkl. MwSt.

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Lieferzeit 1-2 Wochen

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Beschreibung

Explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, difference-in-differences estimation, the front-door method, instrumental variables estimation, and propensity score methods.

Explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, difference-in-differences estimation, the front-door method, instrumental variables estimation, and propensity score methods.

Über den Autor

Babette A. Brumback is Professor and Associate Chair for Education in the Department of Biostatistics at the University of Florida; she won the department's Outstanding Teacher Award for 2020-2021. A Fellow of the American Statistical Association, she has researched and applied methods for causal inference since 1998, specializing in methods for time-dependent confounding, complex survey samples and clustered data.

Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Einband - fest (Hardcover)
ISBN-13: 9780367705053
ISBN-10: 0367705052
Sprache: Englisch
Einband: Gebunden
Autor: Brumback, Babette A.
Hersteller: Taylor & Francis Ltd
Maße: 238 x 159 x 20 mm
Von/Mit: Babette A. Brumback
Erscheinungsdatum: 10.11.2021
Gewicht: 0,528 kg
Artikel-ID: 121393108
Über den Autor

Babette A. Brumback is Professor and Associate Chair for Education in the Department of Biostatistics at the University of Florida; she won the department's Outstanding Teacher Award for 2020-2021. A Fellow of the American Statistical Association, she has researched and applied methods for causal inference since 1998, specializing in methods for time-dependent confounding, complex survey samples and clustered data.

Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2021
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Einband - fest (Hardcover)
ISBN-13: 9780367705053
ISBN-10: 0367705052
Sprache: Englisch
Einband: Gebunden
Autor: Brumback, Babette A.
Hersteller: Taylor & Francis Ltd
Maße: 238 x 159 x 20 mm
Von/Mit: Babette A. Brumback
Erscheinungsdatum: 10.11.2021
Gewicht: 0,528 kg
Artikel-ID: 121393108
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