Barry I. Graubard, Ph.D.
9609 Medical Center Drive
Rockville, MD 20850
Dr. Graubard’s research has primarily focused on the development of statistical methods that efficiently utilize data from surveys and population studies with complex sample designs that can involve sample weighting and stratified multistage cluster sampling. Through collaborative research, he promotes the use of national survey data in DCEG to study etiologic hypotheses. His research includes:
- Survey methods research and its integration into epidemiologic methods
- Development of population genetic methods for analyzing studies with complex samples
- Co-investigative/collaborative epidemiological and cancer surveillance studies
Dr. Graubard received a Ph.D. in mathematics from the University of Maryland in 1991. He began his career as a mathematical statistician at the National Center for Health Statistics in 1977, and held research positions at the Alcohol Drug Abuse and Mental Health Administration and the National Institute of Child Health and Human Development. Dr. Graubard joined the NCI in 1990. He received the American Statistical Association and Biometric Society Snedecor Award for Applied Statistical Research in 1990, is a Fellow of the American Statistical Association, and was selected to be a Fellow of the American Association for the Advancement of Science (AAAS) in 2013.
Graubard BI, Sirken MG. Estimating sibling recurrence risk in population sample surveys. Hum Hered. 2013;76(1):18-27.
Landsman V, Graubard BI. Efficient analysis of case-control studies with sample weights. Stat Med. 2013;32(2):347-60.
Li Y, Graubard BI. Pseudo semiparametric maximum likelihood estimation exploiting gene environment independence for population-based case-control studies with complex samples. Biostatistics. 2012;13(4):711-23.
Gillison ML, Broutian T, Pickard RK, Tong ZY, Xiao W, Kahle L, Graubard BI, Chaturvedi AK. Prevalence of oral HPV infection in the United States, 2009-2010. JAMA. 2012;307(7):693-703.
Landsman V, Lou WY, Graubard BI. Estimating survival probabilities by exposure levels: utilizing vital statistics and complex survey data with mortality follow-up. Stat Med. 2015;34(11):1864-75.
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This page was last updated on June 13th, 2016