Topic: "Causal Inference using Probabilistic Variational Causal Effect in Observational

Studies"

Speaker: Usef Faghihi, Université du Québec à Trois-Rivières

Video link

Recording

 

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In this presentation, I introduce a novel causal analysis methodology called Probabilistic Variational Causal Effect (PACE) designed to evaluate the impact of both rare and common events in observational studies. PACE quantifies the direct causal effects by integrating total variation, which captures the purely causal component, with interventions on varying treatment levels. This integration also incorporates the likelihood of transitions between different treatment states. A key feature of PACE is the parameter d, which allows the metric to emphasize less frequent treatment scenarios when d is low, and more common treatments when d is high, providing a causal effect function dependent on d.

The Compute Ontario Colloquia are weekly Zoom presentations on Advanced Research Computing, High Performance Computing, Research Data Management, and Research Software topics, delivered by staff from three Compute Ontario consortia (CAC, SciNet, SHARCNET) and guest speakers. The series began January 2023 and superseded similar series previously delivered by individual consortia (e.g. General Interest Seminars by SHARCNET or User Group Meeting TechTalks by SciNet). The colloquia are one hour long and include time for questions. No registration is required. Presentations are usually recorded and uploaded to the hosting consortium video channel (colloquia hosted by SHARCNET go to our youtube channel).