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"--

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Bibliographic Details
Main Author: Rosenbaum, Paul R., (Author)
Format: eBook
Language: English
Published: Cambridge, Massachusetts : The MIT Press, [2023]
Series: MIT Press essential knowledge series.
Subjects:
Causation.
Science > Experiments.
Observation (Scientific method)
Inference.
Probabilities.
Mathematical statistics.
elektronické knihy
electronic books
ISBN: 9780262373548
9780262373531
9780262545198
Physical Description: 1 online zdroj (203 stran) : ilustrace.

Cover

Table of contents

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505 0 |a The effects caused by treatments -- Randomized experiments -- Observational studies : the problem -- Adjustments for measured covariates -- Sensitivity to unmeasured covariates -- Quasi-experimental devices in the design of observational studies -- Natural experiments, discontinuities, and instruments -- Replication, resolution and evidence factors -- Uncertainty and complexity in causal inference -- Postscript: Key ideas, chapter by chapter. 
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590 |a IEEE  |b IEEE Xplore MIT Press eBooks Library: Computing & Engineering Collection 
650 0 |a Causation. 
650 0 |a Science  |x Experiments. 
650 0 |a Observation (Scientific method) 
650 0 |a Inference. 
650 0 |a Probabilities. 
650 0 |a Mathematical statistics. 
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