Dealing with Missing Data
The Institute for Policy Research, the Department of Statistics, and the School of Education and Social Policy are pleased to host two lectures.
Professor Donald B. Rubin is the John L. Loeb Professor of Statistics at Harvard University, where he served as chairman of the department of statistics for 13 years. He is most well known for the Rubin Causal Model, a set of methods designed for causal inference with observational data, and for his methods dealing with missing data. He has more than 350 publications, including a number of books, on a variety of topics, including causal inference, techniques for handling missing data, Bayesian methods, multiple imputation, matched sampling, computational methods, survey methods, and applications in many social and biomedical sciences. Rubin is a member of the American Academy of Arts and Sciences, the British Academy, and the National Academy of Sciences, and has received four major awards for statisticians: the Samuel S. Wilks Award of the American Statistical Association, the Parzen Prize for Statistical Innovation, the R. A. Fisher Lectureship, and the George W. Snedecor Award of the Committee of Presidents of Statistical Societies. He is likely the world's most cited living mathematician/statistician, with more than 100,000 citations (per Google Scholar).
For more information, see: http://www.stat.harvard.edu/faculty_page.php?page=rubin.html.
Friday, August 3, 2012
12:00 - 2:15 p.m.
Annenberg Hall, Room 303
2120 Campus Drive, Evanston Campus