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 National Cancer Institute in 1990. He received the American Statistical Association (ASA) and Biometric Society Snedecor Award for Applied Statistical Research in 1990, and he is a Fellow of the American Statistical Association and of the Statistics Section of the American Association for the Advancement of Science. In 2020, he was recognized with the ASA Mentoring Award.
Dr. Graubard’s research interests are primarily in the development and application of statistical methods to efficiently design and analyze studies that make valid inferences to well-defined target populations. These types of studies often collect data using complex sample designs that randomly sample individuals using stratified and multistage cluster sampling. National cross-sectional health surveys and population-based study designs such as case-control studies that sample population controls from the population at risk becoming diseased and case-cohort or nested cohort studies that subsample from a cohort can use complex sample designs. In addition, national health surveys link the participants to vital statistics or electronic medical records to form population representative cohorts to study disease etiology. When analyzing data from these types of studies attention needs to be given to the complex sample design because the sample weights that reflect the differential rates of selection of study participants and the stratification and clustering of the sampling that are used efficient data collection can affect the estimation of prevalence, incidence and risk factor associations of diseases and the variances in analyses. A large part of Dr. Graubard’s research involves the integration of survey methods to develop statistical methods for efficiently using complex sample designs in cancer surveillance and epidemiology.
Areas of Statistical Methods Research
- Augmenting existing samples to address new hypotheses.
- Combining surveys with cohorts, vital statistics, cancer registries and electronic medical records to improve population representativeness of inferences.
- Developing and evaluating disease and mortality absolute risk models with probability and nonprobability samples.
- Inferring health and risk factor disparities between advantaged and disadvantaged groups using national surveys.
- Conducting efficient inferences for genetic data from complex samples.
- Protecting anonymity of participant’s measurements in complex samples.
- Estimation and inference of family aggregation of phenotypes from network sampling in national surveys.
Collaborative Epidemiological and Surveillance Studies
Dr. Graubard collaborates with epidemiologists and other public health researchers on the designs and analyses of a wide range of epidemiologic studies. A large number of these collaborations use the National Health and Nutrition and Examination Survey (NHANES), National Health Interview Survey (NHIS) and the Behavior Risk Factor Survey (BRFS). For instance, Dr. Graubard with his collaborators have used NHANES to study prevalence of human papillomavirus (HPV) and its oncologic subtypes and factors related to increased risk of prevalent HPV, prevalence of monoclonal gammopathy of undetermined significance (MGUS), an associated precursor to multiple myeloma (MM), dietary consumption of food and beverages and nutrition-related biomarkers in relation to development of obesity and chronic disease incidence and all-cause and cause-specific mortality for cancer cardiovascular and other diseases. In addition, they have used the NHIS to study trends in alcohol consumption among the elderly population, trends in race/ethnic disparity in cancer screening, and with NHANES and BRFFS to study trends in physical activity among the elderly.
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