M112 Alway Building, Medical Center
(next to the Dean's courtyard)
|DATE:||February 9, 2017|
|TIME:||1:30 - 2:50 pm|
|TITLE:||It's the Data, Stupid
Professor of Medicine (General Internal Medicine), of Biomedical Data Science,
of Health Research and Policy (Epidemiology)
and Senior Fellow at the Stanford Institute for Economic Policy Research
Much of our attention as data scientists focus on issues of data quality, selection of available covariates for analysis, finding best fitting models for the data, and developing strategies for causal inference where possible. In this talk I focus on the potential for development of datasets themselves. Using the example of the Alcoa dataset on which I have worked for two decades, I demonstrate that what may appear at first blush as a limited data set could, with some foresight, be parlayed into a trove of linked data, opening up myriad research opportunities that may have been entirely obscure at first blush.
Vegso S, Cantley L, Slade M, Taiwo O, Sircar K, Rabinowitz P, Fiellin M, Russi MD, Cullen MR. Extended work hours and risk for acute occupational injury: A case-crossover study of manufacturing workers. AJIM 2007;50:597-603.
Rabinowitz PM, Galusha D, Dixon-Ernst C, Slade MD, Cullen MR. Do ambient noise exposure levels predict hearing loss in an industrial workforce. Occ Environ Med 2007;64:53-59
Taiwo O, Cantley L, Slade M, Pollack KM, Vegso S, Fiellin MG, Cullen MR. Sex differences in Injury Patterns among Workers in Heavy Manufacturing. AJE 2009; 169: 161-6.
Kubo J, Cullen MR, Cantley L, Slade MD, Vegso S, Tessier-Sherman B, Taiwo O, Desai M. Piecewise exponential models to assess the influence of job experience on the hazard of acute injury form hourly factor workers. BMC Research Methods 2013;13(1):89
Neophytou AM, Brown DM, Sostello S, Picciotto S, Noth EM, Hammond K, Cullen MR, Eisen EA. Marginal structural models in occupational epidemiology: An application in a study of ischemic heart disease incidence and PM2.5 in the US aluminum industry. AJE 2014;180:608-15.