ID271: Advanced Regression for Environmental Epidemiology
This course covers applied advanced regression analysis. Its focus is on relaxing classical assumptions in regression analysis to better match what epidemiological data really looks like. Specifically, the course will cover nonlinear exposure-response relationships and repeated measure designs, including non-parametric and semi-parametric smoothing techniques, generalized additive models, and time series models. In addition to the theoretical material, students will apply these techniques using R to actual datasets including modeling the effects of environmental exposures on health outcomes. These techniques also are widely applicable to problems in infectious disease, psychiatric, nutritional, occupational, and cancer epidemiology. Basic biostatistics and a course in regression analysis recommended.
Notes: Basic biostatistics and a course in regression analysis recommended.