## Statistical Science

### A Conversation with Donald B. Rubin

#### Abstract

Donald Bruce Rubin is John L. Loeb Professor of Statistics at Harvard University. He has made fundamental contributions to statistical methods for missing data, causal inference, survey sampling, Bayesian inference, computing and applications to a wide range of disciplines, including psychology, education, policy, law, economics, epidemiology, public health and other social and biomedical sciences.

#### Article information

Source
Statist. Sci., Volume 29, Number 3 (2014), 439-457.

Dates
First available in Project Euclid: 23 September 2014

https://projecteuclid.org/euclid.ss/1411437523

Digital Object Identifier
doi:10.1214/14-STS489

Mathematical Reviews number (MathSciNet)
MR3264555

Zentralblatt MATH identifier
1331.62022

#### Citation

Li, Fan; Mealli, Fabrizia. A Conversation with Donald B. Rubin. Statist. Sci. 29 (2014), no. 3, 439--457. doi:10.1214/14-STS489. https://projecteuclid.org/euclid.ss/1411437523

#### References

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• Rosenbaum, P. R. and Rubin, D. B. (1984b). Sensitivity of Bayes inference with data-dependent stopping rules. Amer. Statist. 38 106–109.
• Rubin, D. B. (1972). A non-iterative algorithm for least squares estimation of missing values in any analysis of variance design. J. R. Stat. Soc. Ser. C. Appl. Stat. 21 136–141.
• Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. J. Educational Psychology 66 688–701.
• Rubin, D. B. (1976). Inference and missing data. Biometrika 63 581–592.
• Rubin, D. B. (1977). Assignment to treatment group on the basis of a covariate. J. Educational Statistics 2 1–26.
• Rubin, D. B. (1978a). Bayesian inference for causal effects: The role of randomization. Ann. Statist. 6 34–58.
• Rubin, D. B. (1978b). Multiple imputations in sample surveys—A phenomenological Bayesian approach to nonresponse (with discussion and reply). In The Proceedings of the Survey Research Methods Section of the American Statistical Association 20–34. Also in Imputation and Editing of Faulty or Missing Survey Data. U.S. Dept. Commerce, Bureau of the Census, Washington, DC.
• Rubin, D. B. (1981). The Bayesian bootstrap. Ann. Statist. 9 130–134.
• Rubin, D. B. (1983). A case study of the robustness of Bayesian methods of inference: Estimating the total in a finite population using transformations to normality. In Scientific Inference, Data Analysis, and Robustness (Madison, Wis., 1981). Publ. Math. Res. Center Univ. Wisconsin 48 213–244. Academic Press, Orlando, FL.
• Rubin, D. B. (1984). Bayesianly justifiable and relevant frequency calculations for the applied statistician. Ann. Statist. 12 1151–1172.
• Rubin, D. B. (1987a). Multiple Imputation for Nonresponse in Surveys. Wiley, New York.
• Rubin, D. B. (1987b). A noniterative sampling/importance resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest: The SIR algorithm. Discussion of “The calculation of posterior distributions by data augmentation” by M. Tanner and W. H. Wong. J. Amer. Statist. Assoc. 82 543–546.
• Rubin, D. B. (1990a). Formal modes of statistical inference for causal effects. J. Statist. Plann. Inference 25 279–292.
• Rubin, D. B. (1990b). Comment on “Neyman (1923) and causal inference in experiments and observational studies.” Statist. Sci. 5 472–480.
• Rubin, D. B. (1994). Comment on “Missing data, imputation, and the bootstrap” by Bradley Efron. J. Amer. Statist. Assoc. 89 475–478.
• Rubin, D. B. (1995). Bayes, Neyman, and calibration. Discussion of Berk, Western and Weiss. Sociological Methodology 25 473–479.
• Rubin, D. B. (1996). Multiple imputation after 18+ years (with discussion and rejoinder). J. Amer. Statist. Assoc. 91 473–517.
• Rubin, D. B. (2002). The ethics of consulting for the tobacco industry. Special issue on “Ethics, statistics and statisticians”. Stat. Methods Med. Res. 11 373–380.
• Rubin, D. B. (2010). Reflections stimulated by the comments of Shadish (2010) and West and Thoemmes (2010). Psychol. Methods 15 38–46.
• Rubin, D. B. (2014a). Converting rejections into positive stimuli. In Past, Present, and Future of Statistical Science (X. Lin et al., eds.) 593–603. CRC Press, New York.
• Rubin, D. B. (2014b). The importance of mentors. In Past, Present, and Future of Statistical Science (X. Lin et al., eds.) 605–613. CRC Press, New York.