Epidemiologic Methods and Data Science: Stronger Together
Abstract: Epidemiologic methods often focus on a statistical model as the main step to getting “the” result. This talk will attempt to widen the perspective on epidemiologic methods. How do we develop and communicate our research plans in a team? How do the numbers from a regression model make it into a table in a manuscript? Practical examples will be shown how standard approaches from data science and free software packages can speed up our work in epidemiology and improve its reproducibility. As a corollary, epidemiology-minded data science might not just need to be a core component in the training of the next generation of epidemiologists, but can in turn also help teach epidemiologic methods.
Bio: Konrad Stopsack leads the Department of Epidemiological Methods and Etiological Research at the Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany. His applied research focuses on molecular and cancer epidemiology. His methodologic and teaching interests include application and further development of epidemiologic methods to improve reproducibility, interpretability, and efficiency of epidemiologic studies.