Causal Vaccine Efficacy Evaluation
Last updated on
Fri, Oct 23, 2020
Nima Hejazi
Assistant Professor of Biostatistics
My research broadly concerns the intersection of causal inference and machine learning, including developing statistical methodology tailored for modern experiments and observational studies in the biomedical and health sciences.
Related
Publications
Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials
The advent and subsequent widespread availability of preventive vaccines has altered the course of public health over the past century. …
Talks
Leveraging the Causal Effects of Stochastic Interventions to Evaluate Vaccine Efficacy in Two-phase Trials
Causal inference has traditionally focused on the effects of static interventions, under which the magnitude of the treatment is set to …
Wed, Jan 20, 2021 12:00 PM
Seattle, Washington, United States (remote due to COVID-19)
Leveraging the Causal Effects of Stochastic Interventions to Evaluate Vaccine Efficacy in Two-phase Trials
Causal inference has traditionally focused on the effects of static interventions, under which the magnitude of the treatment is set to …
Wed, Dec 16, 2020 11:45 AM
Boston, Massachusetts, United States (remote due to COVID-19)
Evaluating the Causal Impacts of Vaccine-induced Immune Responses in Two-phase Vaccine Efficacy Trials
Causal inference has traditionally focused on the effects of static interventions, under which the magnitude of the treatment is set to …
Wed, Nov 4, 2020 1:30 PM
Berkeley, California, United States (remote due to COVID-19)
Evaluating the Causal Impacts of Vaccine-induced Immune Responses in Two-phase Vaccine Efficacy Trials
Causal inference has traditionally focused on the effects of static interventions, under which the magnitude of the treatment is set to …
Thu, Oct 15, 2020 9:00 AM
Berkeley, California, United States (remote due to COVID-19)