Seminars in Causal Inference: Causal effects conditional on post-treatment variables
Tuesday, November 17, 2026 | 14:00-15:00
University of Milano-Bicocca,
Aula Del Consiglio, U7 – 4th floor, Room 4057
Zoom: https://ki-se.zoom.us/j/65583355802
Dr. Mats Stensrud
Institute of Mathematics
Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Many studies aim to estimate treatment effects on outcomes that are defined only for individuals who experience a post-treatment event. For example, the effect of cancer therapies on quality of life is only well defined among individuals who are alive. Similarly, the effect of vaccines on post-infection outcomes is only of interest among individuals who become infected. A naive comparison of outcomes conditional on such post-treatment events generally lacks a causal interpretation, even when treatment is randomly assigned. In this talk, I discuss causal contrasts for outcomes conditional on post-treatment events, including principal stratum effects and conditional separable effects. I then derive identification results for these estimands and discuss their interpretation and the conditions under which they might, in principle, be falsified. I illustrate the relevance of these results for clinical trials of cancer therapies and vaccines, and I conclude by revisiting the classical birth weight paradox in epidemiology.
Dr. Stensrud develops causal and statistical methodology with two main goals: make the target of inference scientifically meaningful, and keep assumptions transparent and testable. He is particularly interested in settings where exposures and outcomes evolve over time (longitudinal and time-to-event data). His works are usually inspired by applications in clinical medicine and epidemiology.