Survival Models and Health Sequences - Department of Statistics - Purdue University Skip to main content
peter_mccullagh_2014.jpg

Myra Samuels Memorial Lecture

Survival Models and Health Sequences

Peter McCullagh
John D. MacArthur Distinguished Service Professor
Department of Statistics, University of Chicago

Start Date and Time: Mon, 7 Apr 2014, 10:30 AM

End Date and Time: Mon, 7 Apr 2014, 11:30 AM

Venue: SC 239

Refreshments: HAAS 111 at 9:45 prior to the lecture

Abstract:

Medical investigations focusing on patient survival often generate not only a failure time for each patient but also a sequence of measurements on patient health at annual or semi-annual check-ups while the patient remains alive. Such a sequence of random length accompanied by a survival time is called a survival process. Ordinarily robust health is associated with longer survival, so the two parts of a survival process cannot be assumed independent. 

This talk is concerned with a general technique — temporal realignment — for constructing statistical models for survival processes. A revival model is a regression model in the sense that it incorporates covariate and treatment effects into both the distribution of survival times and the joint distribution of health outcomes. It also allows the sequence of health outcomes to be used clinically for predicting the subsequent trajectory, including the residual survival time.

Purdue Department of Statistics, 150 N. University St, West Lafayette, IN 47907

Phone: (765) 494-6030, Fax: (765) 494-0558

© 2023 Purdue University | An equal access/equal opportunity university | Copyright Complaints

Trouble with this page? Disability-related accessibility issue? Please contact the College of Science.