Statistics and Biostatistics seminar series
Aaron
Sarvet Link to join seminar: Hosted on Zoom |
Inferential Foundations for Resource-Limited Settings
Emerging scarcity requires new policies for triaging limited resources. However, common-sense counterfactual targets are often impossible to articulate under standard causal models. I will briefly review these standard causal models and discuss their limitations. Then, to make progress, I will elaborate a general potential-outcomes-based framework for evaluating the effects of strategies for allocating a fixed supply of limited resources in a longitudinal setting. I will provide non-parametric conditions that allow identification of counterfactual outcomes from observation of a single cluster (n=1) of patients, and motivate semi-parametric estimators based on likelihood ratio weights. As an illustration, I will consider estimation of survival under counterfactual rules for ventilator triage (including both initiation and termination) in an intensive care unit over the course of a COVID-19 epidemic.