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Rubin, Don / by Andrew Gelman ; edited by Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A. Williams

Author
Gelman, Andrew
Published
London : SAGE Publications Ltd., 2020.
Physical Description
1 online resource
Additional Creators
Atkinson, Paul, 1947-, Delamont, Sara, 1947-, Cernat, Alexandru, Sakshaug, Joseph W., and Williams, Richard A., active 2020
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Summary
Don Rubin (1943-) is a statistician who has made major contributions in statistical modeling, computation, and the foundations of causal inference. Rubin grew up in the Chicago area, studied physics at Princeton University, and received his PhD at Harvard University in 1970. He has worked at the Educational Testing Service and has taught statistics at the University of Wisconsin, University of Chicago, and Harvard University. He is best known, perhaps, for the expectation-maximization (EM) algorithm (a mathematical framework for iterative optimization, which has been useful for mixture models, hierarchical regression, and many other problems for which closed-form solutions are unavailable); multiple imputation as a method for accounting for uncertainty in statistical analysis with missing data; a Bayesian formulation of instrumental variables analysis in economics; propensity ...
Subject(s)
ISBN
9781529745894
9781526421036
Bibliography Note
Includes bibliographical references and index.
View MARC record | catkey: 47378049