TITLE: Credible Causal Inference via Negative controls and Proxies
INSTRUCTOR: Prof. Eric J. Tchetgen Tchetgen, University of Pennsylvania
MODERATOR: Weili He
In this session, we will introduce recent methods for incorporating negative controls and proxy controls to improve the internal validity of observational analyses to infer the causal impact of hypothetical interventions in health and social sciences. The presentation will emphasize conceptual issues around the definition and selection of valid negative controls for detecting potential residual confounding in addition to simple statistical methods leveraging such controls to reduce and possibly eliminate bias due to hidden confounding factors. Throughout, we will consider use cases from pharmaco-epidemiology, infectious disease, clinical epidemiology and environmental epidemiology to illustrate principles of negative controls and their practical potential for improved Real-World Evidence.
Eric J Tchetgen Tchetgen is The Luddy Family President’s Distinguished Professor, Professor of Biostatistics at the Perelman School of Medicine, and Professor of Statistics and Data Science at the Wharton School of the University of Pennsylvania. He also co-directs the Penn Center for Causal Inference, which supports the development and dissemination of causal inference methods in Health and Social Sciences. He has published extensively on Causal Inference, Missing Data and Semiparametric Theory with several impactful applications ranging from HIV research, Genetic Epidemiology, Environmental Health and Alzheimer’s Disease and related aging disorders. He is an Amazon scholar working with Amazon scientists on a variety of causal inference problems in the Tech industry space. Professor Tchetgen Tchetgen is an 2022 inaugural co-recipient of the newly established Rousseeuw Prize for statistics in recognition for his work in Causal Inference with applications in Public Health and Medicine.