Presented by Dave Johnson
Computing PhD, Data Science emphasis
Location: Riverfront Hall (RFH) 102B and via Zoom
Abstract: Discrete-time survival models (DTSMs) are an alternative to the classic Cox proportional hazards models used widely in survival analyses. DTSMs have an (arguably) simpler set of assumptions, and fit many applications without loss of information, in comparison with continuous Cox models—though perhaps at the cost of increased computational complexity. This talk introduces survival analysis in general, DTSMs and their construction in particular, and lastly presents a recent retrospective case study using DTSMs to measure the effect of crowded hospitals on Covid-19 inpatient mortality in Colorado.
Committee: Dr. Michael Perlmutter (Chair), Dr. Edoardo Serra, Dr. Grady Wright, Dr. Donna Calhoun (CompEE)