Big Data Record & the Study of Racial Disparities - Jay Kaufman (McGill University)

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Jay Kaufman2014-1015 PRSS Visiting Scholar

"Big Data Record Linkages for the Study of Racial Disparities in Disease and Mortality"

The increasing availability of vital statistics and other population databases, along with increases in computing power and the capacities of statistical software packages, create opportunities in the synthesis of data resources for answering population-level questions of surveillance and aetiology. Professor Kaufman will review some examples of this kind of work in his own publications, and highlight two current projects: one looking at racial disparities in preterm birth in the US compared to Canada, and the other depicting trajectories in US state-specific mortality disparities.  These projects exemplify some of the promises, successes and limitations of these techniques. Professor Kaufman will use this colloquium to discuss issues of data quality, statistical inference and the choice of study questions.  

Jay Kaufman is Professor and Canada Research Chair in Health Disparities in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University (Montreal, QC). Professor Kaufman's work focuses on social epidemiology, analytic methodology, causal inference and on a variety of health outcomes including reproductive, cardiovascular, psychiatric and infectious diseases.

**The 2014-2015 PRSS Visiting Scholar is co-sponsored with the Center for Africana Studies; Center for Clinical Epidemiology and Biostatistics & Department of Biostatistics and Epidemiology; Office of Inclusion and Diversity, Perelman School of Medicine; and the Department of Sociology.**