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Department Colloquium

Fri., Oct. 27, 2023 3:30 p.m.

Location: Live Stream

Speaker: Janie Coulombe, Université de Montréal

Title:  Recent advances in causal inference under irregular observation times for the outcome (185 kB) PDF file

Zoom Link:

Zoom password: 537905


Electronic health records (EHR) data contain rich information about patients’ health condition, comorbidities, clinical outcomes, and drug prescriptions. They are often used to draw causal inferences about treatment effectiveness. However, these data are not experimental and present with special features that may affect the causal inference when they are not addressed. One of these features is the irregular observation of the longitudinal processes used in the inference. We focus on an irregularly observed longitudinal outcome on which we aim to assess a causal treatment effect. The work on irregularly observed processes in causal inference is relatively recent. In previous work, with co-authors I demonstrated that the irregular observation of the outcome can bias causal effects. In this presentation, I will review why irregular observation times can be problematic, discuss some examples, and present some recent work in this area of research.