Below I provide an overview of past and present course I teach or participate in at McGill, as well as at Erasmus University and the University of Copenhagen. In the sidebar are links to detailed descriptions of current courses.
Presently I teach two courses at McGill: a new PhD-level seminar focused on current substantive and methodological issues in epidemiology, and a course on Impact Evaluation, which I have been co-teaching with Arijit Nandi since 2016.
EPIB 706 is a PhD-level seminar aimed at providing space for students to engage with overarching concepts critical to the theory and practice of epidemiology, as well to explore recent controversies and debates in the field. This course is designed to reinforce formal coursework through making space to develop and sharpen critical thinking skills. We review a selection of papers that range across methods, principles, arguments, and debates in epidemiology and the wider scientific community.
This course covers methods for estimating the effects of social interventions on health outcomes. We introduce and provide the intuition for conducting impact evaluation studies in public and population health and discuss recent methodological developments. We define causal policy effects within the potential outcomes framework and contrast methods for describing associations between an intervention and health outcome with methods for estimating causal effects. We introduce and formally define policy-relevant research questions based on specific causal contrasts. The course format is a mixture of didactic lectures, classroom evaluations of published evaluations, homework assignments, and student presentations. We introduce students to approaches for estimating the effects of social interventions, classified broadly as experimental or observational (quasi-experimental). The section on experimental research covers the use of randomized trials and cluster randomized trials for impact evaluation. The section on observational designs will describe quasi-experimental techniques, including interrupted time series, difference-in-differences, instrumental variables, synthetic control, and regression discontinuity designs.