Donald B. Rubin

E385023

Donald B. Rubin is an influential American statistician best known for developing the Rubin causal model and foundational methods for handling missing data in statistical analysis.

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Donald B. Rubin canonical 1

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Predicate Object
instanceOf American statistician
person
statistician
academicDegree PhD in statistics
almaMater Harvard University
Princeton University
awardReceived ASA Founders Award
Fisher Lectureship
linked to: Fisher Lecture

Parzen Prize for Statistical Innovation
Samuel S. Wilks Memorial Award
birthDate 1943-12-22
doctoralAdvisor William G. Cochran
familyName Rubin
field Bayesian statistics
linked to: Bayesian inference

causal inference
missing data analysis
statistics
survey methodology
givenName Donald
honorificTitle Fellow of the American Statistical Association
Fellow of the Institute of Mathematical Statistics
influenced methods for handling missing data in applied research
modern causal inference in statistics
knownFor Bayesian data analysis
linked to: Bayesian inference

EM algorithm applications
Rubin causal model
Rubin’s rules for combining multiple imputation estimates
foundational methods for handling missing data
multiple imputation
potential outcomes framework for causal inference
propensity score methods
memberOf American Statistical Association
Institute of Mathematical Statistics
International Statistical Institute
name Donald B. Rubin NERFINISHED
nationality United States
notableConcept Rubin causal model
multiple imputation for nonresponse in surveys
propensity score matching
notableWork Causal Inference for Statistics, Social, and Biomedical Sciences
Multiple Imputation for Nonresponse in Surveys
positionHeld John L. Loeb Professor of Statistics
Professor of Statistics at Harvard University
workInstitution Educational Testing Service
Harvard University
University of Chicago
University of Rochester

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Emanuel Parzen notableStudent Donald B. Rubin