Seminar
Mei-Ling Ting Lee, Ph.D
"Threshold Regression for Survival Analysis:
Modeling Event Occurrence When Latent Health Status Decreases to a Threshold"
Considerable research has investigated first hitting times as models for survival and other event times. A first hitting time is the earliest time that a stochastic process reaches a fixed threshold or boundary state. In the medical context, the process represents the latent health status of a subject and the threshold represents a critical level of health that triggers an adverse medical event (relapse, disease onset, death). The time scale can be calendar time or some other operational measure of disease progression. Threshold regression refers to first hitting time models with regression structures that accommodate covariate data. The process, threshold parameters and time scale may all depend on the covariates. Threshold regression methodology has already demonstrated its value in studies of infectious disease, cancer and occupational risk. The model generally does not require the proportional hazards assumption and thus provides an important alternative to this conventional approach. This talk examines aspects of this topic and demonstrates the usefulness of the threshold regression model in practical applications.
