Causal Inference without Randomisation? Quasi-experimental Methods for Public Health Research
Date/Time: 13 April 2017, 13:00-14:00
Venue: Baddiley-Clark Seminar Room
Research in public health which claims to assess the effectiveness of potential interventions needs to establish the existence and magnitude of associated causal effects in order to inform public policy. Observational studies can be affected by unobserved confounding, while randomised control trials are not feasible or ethical in many contexts. In this presentation I discuss quasi-experimental methods for causal inference, which aim to approximate random assignment in observational data. I give an overview of the main models used (including natural experiments, difference-in-differences, instrumental variables, regression discontinuity, and fixed effects), their advantages and disadvantages, and illustrate their application using examples from existing literature. I conclude by discussing the potential for the application of the quasi-experimental approach in public health research.
Mark McGovern is a Lecturer in Economics at Queen’s Management School, Queen’s University Belfast, and the UKCRC Centre of Excellence for Public Health (Northern Ireland). Prior to joining Queen’s in September 2015, he was a Program on the Global Demography of Aging Postdoctoral Fellow at Harvard University. His main research interests are in health and development, including a variety of topics in ageing, HIV, and maternal/child health. His work has involved the application of causal inference methods for observational data to research questions in these areas, such as evaluating the impact of early life conditions on child and adult outcomes. His work has been featured in journals such as the Journal of the American Statistical Association, the Journal of Population Economics, the Journal of Health Economics, Epidemiology, the American Journal of Epidemiology, and the International Journal of Epidemiology. He has collaborated with international agencies including UNAIDS (on methods for dealing with non-ignorable missing data), the Pan-American Health Organisation (on estimating the economic burden of non-communicable disease), and UNICEF (on the long run economic effects of childhood malnutrition). In 2016 he was awarded the Barrington Medal by the Statistical and Social Inquiry Society of Ireland for his research on infant mortality and inequality. He is co-director of CHaRMS – Queen’s University Centre for Health Research at the Management School.