Proportional hazards models with discrete frailty

Description/Abstract

We extend proportional hazards frailty models for lifetime data to allow a negative bi-nomial, Poisson, Geometric or other discrete distribution of the frailty variable. This might represent, for example, the unknown number of flaws in an item under test. Zero frailty corresponds to a limited failure model containing a proportion of units that never fail (long- term survivors). Ways of modifying the model to avoid this are discussed. The models are
applied to a previously published set of data on failures of printed circuit boards and to new data on breaking strengths of samples of cord.