Causal Inference
(Sprache: Englisch)
"Causality is central to the understanding and use of data; without an understanding of cause and effect relationships, we cannot use data to answer important questions in medicine and many other fields"--
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Klappentext zu „Causal Inference “
"Causality is central to the understanding and use of data; without an understanding of cause and effect relationships, we cannot use data to answer important questions in medicine and many other fields"--
Inhaltsverzeichnis zu „Causal Inference “
Series Foreword ixList of Examples xi
List of Methodological Topics xiii
1 The Effects Caused by Treatments 1
2 Randomized Experiments 21
3 Observational Studies: The Problem 47
4 Adjustments for Measured Covariates 67
5 Sensitivity to Unmeasured Covariates 85
6 Quasi-Experimental Devices in the Design of Observational Studies 103
7 Natural Experiments, Discontinuities, and Instruments 117
8 Replication, Resolution, and Evidence Factors 149
9 Uncertainty and Complexity in Causal Inference 159
Postscript: Key Ideas, Chapter by Chapter 175
Glossary 179
Notes 181
Bibliography 189
Further Reading 197
Index 199
Autoren-Porträt von Paul R. Rosenbaum
Paul R. Rosenbaum is the Robert G. Putzel Professor Emeritus of Statistics and Data Science at the Wharton School of the University of Pennsylvania. He is the author of Observation and Experiment: An Introduction to Causal Inference, Design of Observational Studies, Observational Studies, and Replication and Evidence Factors in Observational Studies.
Bibliographische Angaben
- Autor: Paul R. Rosenbaum
- 2023, 224 Seiten, mit Abbildungen, Masse: 13 x 17,8 cm, Taschenbuch, Englisch
- Verlag: The MIT Press
- ISBN-10: 0262545195
- ISBN-13: 9780262545198
- Erscheinungsdatum: 04.04.2023
Sprache:
Englisch
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