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Tenth Annual Demography Graduate Student Methodology Workshop

Missing Data: Theory and Applications

Monday, July 14, 2003
The Nittany Lion Inn, The Pennsylvania State University
Ballroom C

Organized by the PRI Graduate Student Workshop Committee
 Latrica E. Best, Cristina Bradatan, Jacob Cheadle, Mira M. Hidajat, Tanya S. Kenkre, David Warner
Sponsored by
The Population Research Institute (PRI) at Pennsylvania State University

Registration is now CLOSED
Workshop Sessions:
9:00 a.m. Opening and Welcome: Dr. Leif Jensen, Director of Population Research Institute at Pennsylvania State University
9:05-10:05 a.m. "Creating multiply-imputed data sets using incompatible but highly flexible distributions: Application to CDC anthrax vaccine trials," Dr. Donald B. Rubin, Professor and Chair of Statistics at Harvard University
10:05-10:20 a.m. Refreshments
10:20-11:20 a.m. "Missing-data methods for longitudinal research," Dr. Joseph L. Schafer, Associate Professor of Statistics at Pennsylvania State University
11:20-12:30 p.m. "Analysis of coarsened longitudinal data using multiple imputation," Dr. Trivellore Raghunathan, Associate Professor of Biostatistics and Senior Associate Research Scientist of the Institute for Social Research (ISR) at the University of Michigan
12:30-1:30 p.m. Informal luncheon with the speakers


Registration is CLOSED

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If you need to cancel your registration, please send an email to workshop_reg@pop.psu.edu with the subject heading WORKSHOP CANCELLATION.

A brief introduction of the three speakers and the discussant:

Donald B. Rubin received his Ph. D. in Statistics from Harvard in 1970, and has been Professor of Statistics at Harvard since 1984. He is author of Multiple Imputation for Nonresponse in Surveys (1987) and co-author of Statistical Analysis with Missing Data (1987) and Bayesian Data Analysis (1995). He has published more than 200 articles and reviews.

Trivellore Raghunathan received his Ph.D. in statistics from Harvard University in 1987. His main research interests are in design and analysis of sample surveys, analysis of missing data, masking public release data for confidentiality purposes, Bayesian and statistical methods for epidemiological research. He teaches courses on methods to compensate for missing data, analysis of data from longitudinal studies, statistical methods for epidemiology, Bayesian methods, survey sample design, and analysis of complex survey data.

Joseph L. Schafer received his Ph.D. in Statistics from Harvard in 1991. He has developed techniques for analyzing incomplete data and incorporating missing-data uncertainty into statistical inference. These techniques include both asymptotic approximations and simulation via multiple imputations, in which missing data are replaced by multiple simulated values. He has worked to develop general-purpose algorithms and software for the analysis of incomplete multivariate data. For a list of his main publications, please click here.


For more information, please contact workshop@pop.psu.edu


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